Loan_dataset

Dataset statistics

Number of variables	45
Number of observations	24999
Missing cells	72599
Missing cells (%)	6.5%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	8.6 MiB
Average record size in memory	360.0 B

Variable types

Numeric	23
Categorical	22

Alerts

`int_rate` has a high cardinality: 361 distinct values	High cardinality
`emp_title` has a high cardinality: 19952 distinct values	High cardinality
`issue_d` has a high cardinality: 55 distinct values	High cardinality
`desc` has a high cardinality: 16661 distinct values	High cardinality
`title` has a high cardinality: 12893 distinct values	High cardinality
`zip_code` has a high cardinality: 787 distinct values	High cardinality
`earliest_cr_line` has a high cardinality: 495 distinct values	High cardinality
`revol_util` has a high cardinality: 1059 distinct values	High cardinality
`last_pymnt_d` has a high cardinality: 101 distinct values	High cardinality
`last_credit_pull_d` has a high cardinality: 102 distinct values	High cardinality
`loan_amnt` is highly correlated with `funded_amnt` and 6 other fields	High correlation
`funded_amnt` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`funded_amnt_inv` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`installment` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`delinq_2yrs` is highly correlated with `mths_since_last_delinq`	High correlation
`mths_since_last_delinq` is highly correlated with `delinq_2yrs` and 1 other fields	High correlation
`mths_since_last_record` is highly correlated with `mths_since_last_delinq` and 2 other fields	High correlation
`open_acc` is highly correlated with `total_acc`	High correlation
`pub_rec` is highly correlated with `mths_since_last_record` and 1 other fields	High correlation
`total_acc` is highly correlated with `open_acc`	High correlation
`out_prncp` is highly correlated with `out_prncp_inv`	High correlation
`out_prncp_inv` is highly correlated with `out_prncp`	High correlation
`total_pymnt` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`total_pymnt_inv` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`total_rec_prncp` is highly correlated with `loan_amnt` and 7 other fields	High correlation
`total_rec_int` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`recoveries` is highly correlated with `collection_recovery_fee`	High correlation
`collection_recovery_fee` is highly correlated with `recoveries`	High correlation
`last_pymnt_amnt` is highly correlated with `total_rec_prncp`	High correlation
`pub_rec_bankruptcies` is highly correlated with `mths_since_last_record` and 1 other fields	High correlation
`loan_amnt` is highly correlated with `funded_amnt` and 6 other fields	High correlation
`funded_amnt` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`funded_amnt_inv` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`installment` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`delinq_2yrs` is highly correlated with `mths_since_last_delinq`	High correlation
`mths_since_last_delinq` is highly correlated with `delinq_2yrs`	High correlation
`mths_since_last_record` is highly correlated with `pub_rec` and 1 other fields	High correlation
`open_acc` is highly correlated with `total_acc`	High correlation
`pub_rec` is highly correlated with `mths_since_last_record` and 1 other fields	High correlation
`total_acc` is highly correlated with `open_acc`	High correlation
`out_prncp` is highly correlated with `out_prncp_inv`	High correlation
`out_prncp_inv` is highly correlated with `out_prncp`	High correlation
`total_pymnt` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`total_pymnt_inv` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`total_rec_prncp` is highly correlated with `loan_amnt` and 7 other fields	High correlation
`total_rec_int` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`recoveries` is highly correlated with `collection_recovery_fee`	High correlation
`collection_recovery_fee` is highly correlated with `recoveries`	High correlation
`last_pymnt_amnt` is highly correlated with `total_rec_prncp`	High correlation
`pub_rec_bankruptcies` is highly correlated with `mths_since_last_record` and 1 other fields	High correlation
`loan_amnt` is highly correlated with `funded_amnt` and 6 other fields	High correlation
`funded_amnt` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`funded_amnt_inv` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`installment` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`delinq_2yrs` is highly correlated with `mths_since_last_delinq`	High correlation
`mths_since_last_delinq` is highly correlated with `delinq_2yrs`	High correlation
`mths_since_last_record` is highly correlated with `pub_rec` and 1 other fields	High correlation
`open_acc` is highly correlated with `total_acc`	High correlation
`pub_rec` is highly correlated with `mths_since_last_record` and 1 other fields	High correlation
`total_acc` is highly correlated with `open_acc`	High correlation
`out_prncp` is highly correlated with `out_prncp_inv`	High correlation
`out_prncp_inv` is highly correlated with `out_prncp`	High correlation
`total_pymnt` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`total_pymnt_inv` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`total_rec_prncp` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`total_rec_int` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`recoveries` is highly correlated with `collection_recovery_fee`	High correlation
`collection_recovery_fee` is highly correlated with `recoveries`	High correlation
`pub_rec_bankruptcies` is highly correlated with `mths_since_last_record` and 1 other fields	High correlation
`loan_status` is highly correlated with `next_pymnt_d`	High correlation
`pub_rec` is highly correlated with `pub_rec_bankruptcies`	High correlation
`grade` is highly correlated with `sub_grade`	High correlation
`next_pymnt_d` is highly correlated with `loan_status` and 1 other fields	High correlation
`term` is highly correlated with `next_pymnt_d`	High correlation
`pub_rec_bankruptcies` is highly correlated with `pub_rec`	High correlation
`sub_grade` is highly correlated with `grade`	High correlation
`loan_amnt` is highly correlated with `funded_amnt` and 7 other fields	High correlation
`funded_amnt` is highly correlated with `loan_amnt` and 7 other fields	High correlation
`funded_amnt_inv` is highly correlated with `loan_amnt` and 8 other fields	High correlation
`term` is highly correlated with `sub_grade` and 1 other fields	High correlation
`installment` is highly correlated with `loan_amnt` and 6 other fields	High correlation
`grade` is highly correlated with `sub_grade`	High correlation
`sub_grade` is highly correlated with `term` and 2 other fields	High correlation
`issue_d` is highly correlated with `mths_since_last_record`	High correlation
`loan_status` is highly correlated with `out_prncp` and 1 other fields	High correlation
`mths_since_last_record` is highly correlated with `funded_amnt_inv` and 3 other fields	High correlation
`open_acc` is highly correlated with `total_acc`	High correlation
`pub_rec` is highly correlated with `mths_since_last_record` and 1 other fields	High correlation
`total_acc` is highly correlated with `open_acc`	High correlation
`out_prncp` is highly correlated with `loan_status` and 2 other fields	High correlation
`out_prncp_inv` is highly correlated with `loan_status` and 2 other fields	High correlation
`total_pymnt` is highly correlated with `loan_amnt` and 7 other fields	High correlation
`total_pymnt_inv` is highly correlated with `loan_amnt` and 7 other fields	High correlation
`total_rec_prncp` is highly correlated with `loan_amnt` and 7 other fields	High correlation
`total_rec_int` is highly correlated with `loan_amnt` and 10 other fields	High correlation
`recoveries` is highly correlated with `collection_recovery_fee`	High correlation
`collection_recovery_fee` is highly correlated with `recoveries`	High correlation
`last_pymnt_amnt` is highly correlated with `loan_amnt` and 5 other fields	High correlation
`pub_rec_bankruptcies` is highly correlated with `mths_since_last_record` and 1 other fields	High correlation
`desc` has 8192 (32.8%) missing values	Missing
`mths_since_last_delinq` has 16240 (65.0%) missing values	Missing
`mths_since_last_record` has 23320 (93.3%) missing values	Missing
`next_pymnt_d` has 24301 (97.2%) missing values	Missing
`pub_rec_bankruptcies` has 417 (1.7%) missing values	Missing
`annual_inc` is highly skewed (γ1 = 36.3657122)	Skewed
`collection_recovery_fee` is highly skewed (γ1 = 23.05081549)	Skewed
`delinq_2yrs` has 22317 (89.3%) zeros	Zeros
`inq_last_6mths` has 12185 (48.7%) zeros	Zeros
`mths_since_last_delinq` has 260 (1.0%) zeros	Zeros
`mths_since_last_record` has 404 (1.6%) zeros	Zeros
`revol_bal` has 621 (2.5%) zeros	Zeros
`out_prncp` has 24301 (97.2%) zeros	Zeros
`out_prncp_inv` has 24301 (97.2%) zeros	Zeros
`total_rec_late_fee` has 23744 (95.0%) zeros	Zeros
`recoveries` has 22375 (89.5%) zeros	Zeros
`collection_recovery_fee` has 22634 (90.5%) zeros	Zeros

Reproduction

Analysis started	2021-10-21 17:29:50.461451
Analysis finished	2021-10-21 17:31:48.614703
Duration	1 minute and 58.15 seconds
Software version	pandas-profiling v3.1.1
Download configuration	config.json

loan_amnt
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	781
Distinct (%)	3.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	11262.4985

Minimum	500
Maximum	35000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	500
5-th percentile	2400
Q1	5562.5
median	10000
Q3	15000
95-th percentile	25000
Maximum	35000
Range	34500
Interquartile range (IQR)	9437.5

Descriptive statistics

Standard deviation	7391.976258
Coefficient of variation (CV)	0.6563353822
Kurtosis	0.7453467735
Mean	11262.4985
Median Absolute Deviation (MAD)	5000
Skewness	1.043139418
Sum	281551200
Variance	54641313
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
10000	1804	7.2%
12000	1508	6.0%
5000	1259	5.0%
6000	1225	4.9%
15000	1195	4.8%
20000	1039	4.2%
8000	964	3.9%
25000	887	3.5%
4000	683	2.7%
3000	650	2.6%
Other values (771)	13785	55.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
500	2	< 0.1%
900	2	< 0.1%
950	1	< 0.1%
1000	166	0.7%
1050	3	< 0.1%
1100	3	< 0.1%
1125	1	< 0.1%
1150	1	< 0.1%
1200	85	0.3%
1250	6	< 0.1%

Value	Count	Frequency (%)
35000	398	1.6%
34800	2	< 0.1%
34525	1	< 0.1%
34475	4	< 0.1%
34200	1	< 0.1%
34000	11	< 0.1%
33950	5	< 0.1%
33600	4	< 0.1%
33500	1	< 0.1%
33250	1	< 0.1%

funded_amnt
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	951
Distinct (%)	3.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	10985.0994

Minimum	500
Maximum	35000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	500
5-th percentile	2400
Q1	5500
median	10000
Q3	15000
95-th percentile	25000
Maximum	35000
Range	34500
Interquartile range (IQR)	9500

Descriptive statistics

Standard deviation	7123.122668
Coefficient of variation (CV)	0.648434976
Kurtosis	0.9385199004
Mean	10985.0994
Median Absolute Deviation (MAD)	5000
Skewness	1.071784771
Sum	274616500
Variance	50738876.54
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
10000	1750	7.0%
12000	1453	5.8%
5000	1253	5.0%
6000	1219	4.9%
15000	1119	4.5%
8000	955	3.8%
20000	919	3.7%
25000	725	2.9%
4000	682	2.7%
3000	646	2.6%
Other values (941)	14278	57.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
500	2	< 0.1%
900	2	< 0.1%
950	1	< 0.1%
1000	166	0.7%
1050	3	< 0.1%
1100	3	< 0.1%
1125	1	< 0.1%
1150	1	< 0.1%
1200	87	0.3%
1250	6	< 0.1%

Value	Count	Frequency (%)
35000	330	1.3%
34800	1	< 0.1%
34525	1	< 0.1%
34475	3	< 0.1%
34250	1	< 0.1%
34000	10	< 0.1%
33950	4	< 0.1%
33600	4	< 0.1%
33500	1	< 0.1%
33250	1	< 0.1%

funded_amnt_inv
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5518
Distinct (%)	22.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	10435.34441

Minimum	0
Maximum	35000
Zeros	87
Zeros (%)	0.3%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	0
5-th percentile	2000
Q1	5000
median	9000
Q3	14400
95-th percentile	24700
Maximum	35000
Range	35000
Interquartile range (IQR)	9400

Descriptive statistics

Standard deviation	7064.11343
Coefficient of variation (CV)	0.676941091
Kurtosis	1.06142007
Mean	10435.34441
Median Absolute Deviation (MAD)	4200
Skewness	1.095251814
Sum	260873174.9
Variance	49901698.55
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
10000	822	3.3%
5000	805	3.2%
6000	773	3.1%
12000	695	2.8%
8000	533	2.1%
3000	510	2.0%
4000	479	1.9%
15000	411	1.6%
7000	379	1.5%
2000	280	1.1%
Other values (5508)	19312	77.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	87	0.3%
0.000654607	1	< 0.1%
0.001867696	1	< 0.1%
0.001963093	1	< 0.1%
0.002283598	1	< 0.1%
0.002373058	1	< 0.1%
0.002915021	1	< 0.1%
0.003084491	1	< 0.1%
0.00310016	1	< 0.1%
0.00435368	1	< 0.1%

Value	Count	Frequency (%)
35000	81	0.3%
34993.65539	1	< 0.1%
34993.32571	1	< 0.1%
34993.19696	1	< 0.1%
34987.98452	1	< 0.1%
34977.34674	1	< 0.1%
34975.81636	1	< 0.1%
34975	51	0.2%
34972.35245	1	< 0.1%
34972.12183	1	< 0.1%

term
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	195.4 KiB

36 months	18203
60 months	6796

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	249990
Distinct characters	10
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	36 months
2nd row	36 months
3rd row	36 months
4th row	60 months
5th row	60 months

Common Values

Value	Count	Frequency (%)
36 months	18203	72.8%
60 months	6796	27.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
months	24999	50.0%
36	18203	36.4%
60	6796	13.6%

Most occurring characters

Value	Count	Frequency (%)
	49998	20.0%
s	24999	10.0%
h	24999	10.0%
t	24999	10.0%
n	24999	10.0%
o	24999	10.0%
m	24999	10.0%
6	24999	10.0%
3	18203	7.3%
0	6796	2.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	149994	60.0%
Space Separator	49998	20.0%
Decimal Number	49998	20.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
s	24999	16.7%
h	24999	16.7%
t	24999	16.7%
n	24999	16.7%
o	24999	16.7%
m	24999	16.7%

Decimal Number

Value	Count	Frequency (%)
6	24999	50.0%
3	18203	36.4%
0	6796	13.6%

Space Separator

Value	Count	Frequency (%)
	49998	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	149994	60.0%
Common	99996	40.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
s	24999	16.7%
h	24999	16.7%
t	24999	16.7%
n	24999	16.7%
o	24999	16.7%
m	24999	16.7%

Common

Value	Count	Frequency (%)
	49998	50.0%
6	24999	25.0%
3	18203	18.2%
0	6796	6.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	249990	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	49998	20.0%
s	24999	10.0%
h	24999	10.0%
t	24999	10.0%
n	24999	10.0%
o	24999	10.0%
m	24999	10.0%
6	24999	10.0%
3	18203	7.3%
0	6796	2.7%

int_rate
Categorical

HIGH CARDINALITY

Distinct	361
Distinct (%)	1.4%
Missing	0
Missing (%)	0.0%
Memory size	195.4 KiB

10.99%	602
13.49%	520
11.49%	499
7.51%	496
7.88%	476
Other values (356)	22406

Length

Max length	6
Median length	6
Mean length	5.697067883
Min length	5

Characters and Unicode

Total characters	142421
Distinct characters	12
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	28 ?
Unique (%)	0.1%

Sample

1st row	7.51%
2nd row	8.94%
3rd row	13.57%
4th row	20.89%
5th row	17.49%

Common Values

Value	Count	Frequency (%)
10.99%	602	2.4%
13.49%	520	2.1%
11.49%	499	2.0%
7.51%	496	2.0%
7.88%	476	1.9%
7.49%	427	1.7%
11.71%	374	1.5%
9.99%	367	1.5%
11.99%	360	1.4%
5.42%	355	1.4%
Other values (351)	20523	82.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
10.99	602	2.4%
13.49	520	2.1%
11.49	499	2.0%
7.51	496	2.0%
7.88	476	1.9%
7.49	427	1.7%
11.71	374	1.5%
9.99	367	1.5%
11.99	360	1.4%
5.42	355	1.4%
Other values (351)	20523	82.1%

Most occurring characters

Value	Count	Frequency (%)
%	24999	17.6%
.	24999	17.6%
1	23989	16.8%
9	13742	9.6%
2	8063	5.7%
6	7636	5.4%
7	7588	5.3%
4	7038	4.9%
5	6286	4.4%
3	6230	4.4%
Other values (2)	11851	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	92423	64.9%
Other Punctuation	49998	35.1%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	23989	26.0%
9	13742	14.9%
2	8063	8.7%
6	7636	8.3%
7	7588	8.2%
4	7038	7.6%
5	6286	6.8%
3	6230	6.7%
8	6022	6.5%
0	5829	6.3%

Other Punctuation

Value	Count	Frequency (%)
%	24999	50.0%
.	24999	50.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	142421	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
%	24999	17.6%
.	24999	17.6%
1	23989	16.8%
9	13742	9.6%
2	8063	5.7%
6	7636	5.4%
7	7588	5.3%
4	7038	4.9%
5	6286	4.4%
3	6230	4.4%
Other values (2)	11851	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	142421	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
%	24999	17.6%
.	24999	17.6%
1	23989	16.8%
9	13742	9.6%
2	8063	5.7%
6	7636	5.4%
7	7588	5.3%
4	7038	4.9%
5	6286	4.4%
3	6230	4.4%
Other values (2)	11851	8.3%

installment
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	11618
Distinct (%)	46.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	325.5068243

Minimum	16.08
Maximum	1305.19
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	16.08
5-th percentile	73.928
Q1	168.64
median	283.2
Q3	431.25
95-th percentile	753.51
Maximum	1305.19
Range	1289.11
Interquartile range (IQR)	262.61

Descriptive statistics

Standard deviation	206.9950526
Coefficient of variation (CV)	0.6359161686
Kurtosis	1.230732774
Mean	325.5068243
Median Absolute Deviation (MAD)	122.73
Skewness	1.115339594
Sum	8137345.1
Variance	42846.95178
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
311.11	47	0.2%
311.02	35	0.1%
180.96	35	0.1%
339.31	30	0.1%
187.69	30	0.1%
186.61	30	0.1%
312.82	29	0.1%
303.27	28	0.1%
368.45	27	0.1%
373.33	27	0.1%
Other values (11608)	24681	98.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
16.08	1	< 0.1%
16.47	1	< 0.1%
21.25	1	< 0.1%
21.99	1	< 0.1%
22.24	1	< 0.1%
22.94	1	< 0.1%
23.17	1	< 0.1%
23.51	1	< 0.1%
24.16	1	< 0.1%
24.27	1	< 0.1%

Value	Count	Frequency (%)
1305.19	1	< 0.1%
1295.21	1	< 0.1%
1288.1	1	< 0.1%
1283.5	1	< 0.1%
1276.6	2	< 0.1%
1272.2	1	< 0.1%
1269.73	3	< 0.1%
1265.16	1	< 0.1%
1263.23	1	< 0.1%
1257.98	2	< 0.1%

grade
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	195.4 KiB

B	7497
A	6293
C	5090
D	3431
E	1804
Other values (2)	884

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	24999
Distinct characters	7
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	A
2nd row	A
3rd row	C
4th row	F
5th row	D

Common Values

Value	Count	Frequency (%)
B	7497	30.0%
A	6293	25.2%
C	5090	20.4%
D	3431	13.7%
E	1804	7.2%
F	678	2.7%
G	206	0.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
b	7497	30.0%
a	6293	25.2%
c	5090	20.4%
d	3431	13.7%
e	1804	7.2%
f	678	2.7%
g	206	0.8%

Most occurring characters

Value	Count	Frequency (%)
B	7497	30.0%
A	6293	25.2%
C	5090	20.4%
D	3431	13.7%
E	1804	7.2%
F	678	2.7%
G	206	0.8%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	24999	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
B	7497	30.0%
A	6293	25.2%
C	5090	20.4%
D	3431	13.7%
E	1804	7.2%
F	678	2.7%
G	206	0.8%

Most occurring scripts

Value	Count	Frequency (%)
Latin	24999	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
B	7497	30.0%
A	6293	25.2%
C	5090	20.4%
D	3431	13.7%
E	1804	7.2%
F	678	2.7%
G	206	0.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	24999	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
B	7497	30.0%
A	6293	25.2%
C	5090	20.4%
D	3431	13.7%
E	1804	7.2%
F	678	2.7%
G	206	0.8%

sub_grade
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	35
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	195.4 KiB

A4	1831
B3	1777
A5	1757
B5	1732
B4	1573
Other values (30)	16329

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	49998
Distinct characters	12
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	A4
2nd row	A5
3rd row	C3
4th row	F1
5th row	D5

Common Values

Value	Count	Frequency (%)
A4	1831	7.3%
B3	1777	7.1%
A5	1757	7.0%
B5	1732	6.9%
B4	1573	6.3%
C1	1338	5.4%
B2	1290	5.2%
C2	1267	5.1%
B1	1125	4.5%
A3	1107	4.4%
Other values (25)	10202	40.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
a4	1831	7.3%
b3	1777	7.1%
a5	1757	7.0%
b5	1732	6.9%
b4	1573	6.3%
c1	1338	5.4%
b2	1290	5.2%
c2	1267	5.1%
b1	1125	4.5%
a3	1107	4.4%
Other values (25)	10202	40.8%

Most occurring characters

Value	Count	Frequency (%)
B	7497	15.0%
A	6293	12.6%
4	5225	10.5%
5	5164	10.3%
3	5105	10.2%
C	5090	10.2%
2	4978	10.0%
1	4527	9.1%
D	3431	6.9%
E	1804	3.6%
Other values (2)	884	1.8%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	24999	50.0%
Decimal Number	24999	50.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
B	7497	30.0%
A	6293	25.2%
C	5090	20.4%
D	3431	13.7%
E	1804	7.2%
F	678	2.7%
G	206	0.8%

Decimal Number

Value	Count	Frequency (%)
4	5225	20.9%
5	5164	20.7%
3	5105	20.4%
2	4978	19.9%
1	4527	18.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	24999	50.0%
Common	24999	50.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
B	7497	30.0%
A	6293	25.2%
C	5090	20.4%
D	3431	13.7%
E	1804	7.2%
F	678	2.7%
G	206	0.8%

Common

Value	Count	Frequency (%)
4	5225	20.9%
5	5164	20.7%
3	5105	20.4%
2	4978	19.9%
1	4527	18.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	49998	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
B	7497	15.0%
A	6293	12.6%
4	5225	10.5%
5	5164	10.3%
3	5105	10.2%
C	5090	10.2%
2	4978	10.0%
1	4527	9.1%
D	3431	6.9%
E	1804	3.6%
Other values (2)	884	1.8%

emp_title
Categorical

HIGH CARDINALITY

Distinct	19952
Distinct (%)	79.8%
Missing	6
Missing (%)	< 0.1%
Memory size	195.4 KiB

Bank of America	109
IBM	66
AT&T	59
Kaiser Permanente	56
Lockheed Martin	44
Other values (19947)	24659

Length

Max length	78
Median length	18
Mean length	18.51074301
Min length	2

Characters and Unicode

Total characters	462639
Distinct characters	92
Distinct categories	14 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	17797 ?
Unique (%)	71.2%

Sample

1st row	15
2nd row	1400
3rd row	36000
4th row	553742017
5th row	old palm inc

Common Values

Value	Count	Frequency (%)
Bank of America	109	0.4%
IBM	66	0.3%
AT&T	59	0.2%
Kaiser Permanente	56	0.2%
Lockheed Martin	44	0.2%
JP Morgan Chase	37	0.1%
Department of Defense	36	0.1%
JPMorgan Chase	36	0.1%
Booz Allen Hamilton	34	0.1%
Northrop Grumman	34	0.1%
Other values (19942)	24482	97.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
inc	2262	3.4%
of	1949	2.9%
	871	1.3%
and	701	1.0%
county	613	0.9%
city	606	0.9%
services	564	0.8%
bank	554	0.8%
center	547	0.8%
school	496	0.7%
Other values (14290)	58283	86.4%

Most occurring characters

Value	Count	Frequency (%)
	43475	9.4%
e	37182	8.0%
a	30148	6.5%
n	29875	6.5%
o	29182	6.3%
i	27145	5.9%
r	26863	5.8%
t	25507	5.5%
s	20030	4.3%
l	17960	3.9%
Other values (82)	175272	37.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	331474	71.6%
Uppercase Letter	80137	17.3%
Space Separator	43475	9.4%
Other Punctuation	5920	1.3%
Decimal Number	768	0.2%
Dash Punctuation	643	0.1%
Open Punctuation	101	< 0.1%
Close Punctuation	99	< 0.1%
Math Symbol	14	< 0.1%
Other Symbol	2	< 0.1%
Other values (4)	6	< 0.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
C	11070	13.8%
A	6545	8.2%
S	6044	7.5%
I	5555	6.9%
M	5074	6.3%
L	4265	5.3%
P	4187	5.2%
B	3962	4.9%
E	3941	4.9%
D	3910	4.9%
Other values (18)	25584	31.9%

Lowercase Letter

Value	Count	Frequency (%)
e	37182	11.2%
a	30148	9.1%
n	29875	9.0%
o	29182	8.8%
i	27145	8.2%
r	26863	8.1%
t	25507	7.7%
s	20030	6.0%
l	17960	5.4%
c	16174	4.9%
Other values (17)	71408	21.5%

Other Punctuation

Value	Count	Frequency (%)
.	2657	44.9%
,	1542	26.0%
&	988	16.7%
'	460	7.8%
/	211	3.6%
#	27	0.5%
@	7	0.1%
"	7	0.1%
:	5	0.1%
!	5	0.1%
Other values (4)	11	0.2%

Decimal Number

Value	Count	Frequency (%)
1	160	20.8%
2	134	17.4%
3	118	15.4%
0	78	10.2%
4	74	9.6%
5	56	7.3%
6	45	5.9%
9	43	5.6%
7	35	4.6%
8	25	3.3%

Open Punctuation

Value	Count	Frequency (%)
(	100	99.0%
[	1	1.0%

Math Symbol

Value	Count	Frequency (%)
+	13	92.9%
\|	1	7.1%

Currency Symbol

Value	Count	Frequency (%)
$	1	50.0%
¢	1	50.0%

Space Separator

Value	Count	Frequency (%)
	43475	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	643	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	99	100.0%

Other Symbol

Value	Count	Frequency (%)
©	2	100.0%

Other Number

Value	Count	Frequency (%)
²	2	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	1	100.0%

Control

Value	Count	Frequency (%)
	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	411611	89.0%
Common	51028	11.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	37182	9.0%
a	30148	7.3%
n	29875	7.3%
o	29182	7.1%
i	27145	6.6%
r	26863	6.5%
t	25507	6.2%
s	20030	4.9%
l	17960	4.4%
c	16174	3.9%
Other values (45)	151545	36.8%

Common

Value	Count	Frequency (%)
	43475	85.2%
.	2657	5.2%
,	1542	3.0%
&	988	1.9%
-	643	1.3%
'	460	0.9%
/	211	0.4%
1	160	0.3%
2	134	0.3%
3	118	0.2%
Other values (27)	640	1.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	462629	> 99.9%
None	10	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	43475	9.4%
e	37182	8.0%
a	30148	6.5%
n	29875	6.5%
o	29182	6.3%
i	27145	5.9%
r	26863	5.8%
t	25507	5.5%
s	20030	4.3%
l	17960	3.9%
Other values (75)	175262	37.9%

None

Value	Count	Frequency (%)
©	2	20.0%
²	2	20.0%
Ã	2	20.0%
Â	1	10.0%
¢	1	10.0%
	1	10.0%
â	1	10.0%

emp_length
Categorical

Distinct	11
Distinct (%)	< 0.1%
Missing	41
Missing (%)	0.2%
Memory size	195.4 KiB

10+ years	5565
2 years	2871
< 1 year	2864
3 years	2723
4 years	2282
Other values (6)	8653

Length

Max length	9
Median length	7
Mean length	7.475719208
Min length	6

Characters and Unicode

Total characters	186579
Distinct characters	18
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	10+ years
2nd row	1 year
3rd row	4 years
4th row	10+ years
5th row	5 years

Common Values

Value	Count	Frequency (%)
10+ years	5565	22.3%
2 years	2871	11.5%
< 1 year	2864	11.5%
3 years	2723	10.9%
4 years	2282	9.1%
5 years	2150	8.6%
1 year	2121	8.5%
6 years	1427	5.7%
7 years	1145	4.6%
8 years	970	3.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
years	19973	37.8%
10	5565	10.5%
year	4985	9.4%
1	4985	9.4%
2	2871	5.4%
	2864	5.4%
3	2723	5.2%
4	2282	4.3%
5	2150	4.1%
6	1427	2.7%
Other values (3)	2955	5.6%

Most occurring characters

Value	Count	Frequency (%)
	27822	14.9%
r	24958	13.4%
y	24958	13.4%
e	24958	13.4%
a	24958	13.4%
s	19973	10.7%
1	10550	5.7%
+	5565	3.0%
0	5565	3.0%
2	2871	1.5%
Other values (8)	14401	7.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	119805	64.2%
Decimal Number	30523	16.4%
Space Separator	27822	14.9%
Math Symbol	8429	4.5%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	10550	34.6%
0	5565	18.2%
2	2871	9.4%
3	2723	8.9%
4	2282	7.5%
5	2150	7.0%
6	1427	4.7%
7	1145	3.8%
8	970	3.2%
9	840	2.8%

Lowercase Letter

Value	Count	Frequency (%)
r	24958	20.8%
y	24958	20.8%
e	24958	20.8%
a	24958	20.8%
s	19973	16.7%

Math Symbol

Value	Count	Frequency (%)
+	5565	66.0%
<	2864	34.0%

Space Separator

Value	Count	Frequency (%)
	27822	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	119805	64.2%
Common	66774	35.8%

Most frequent character per script

Common

Value	Count	Frequency (%)
	27822	41.7%
1	10550	15.8%
+	5565	8.3%
0	5565	8.3%
2	2871	4.3%
<	2864	4.3%
3	2723	4.1%
4	2282	3.4%
5	2150	3.2%
6	1427	2.1%
Other values (3)	2955	4.4%

Latin

Value	Count	Frequency (%)
r	24958	20.8%
y	24958	20.8%
e	24958	20.8%
a	24958	20.8%
s	19973	16.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	186579	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	27822	14.9%
r	24958	13.4%
y	24958	13.4%
e	24958	13.4%
a	24958	13.4%
s	19973	10.7%
1	10550	5.7%
+	5565	3.0%
0	5565	3.0%
2	2871	1.5%
Other values (8)	14401	7.7%

home_ownership
Categorical

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	195.4 KiB

RENT	12034
MORTGAGE	11118
OWN	1785
OTHER	62

Length

Max length	8
Median length	4
Mean length	5.710028401
Min length	3

Characters and Unicode

Total characters	142745
Distinct characters	10
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	RENT
2nd row	RENT
3rd row	OWN
4th row	MORTGAGE
5th row	MORTGAGE

Common Values

Value	Count	Frequency (%)
RENT	12034	48.1%
MORTGAGE	11118	44.5%
OWN	1785	7.1%
OTHER	62	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
rent	12034	48.1%
mortgage	11118	44.5%
own	1785	7.1%
other	62	0.2%

Most occurring characters

Value	Count	Frequency (%)
T	23214	16.3%
E	23214	16.3%
R	23214	16.3%
G	22236	15.6%
N	13819	9.7%
O	12965	9.1%
A	11118	7.8%
M	11118	7.8%
W	1785	1.3%
H	62	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	142745	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
T	23214	16.3%
E	23214	16.3%
R	23214	16.3%
G	22236	15.6%
N	13819	9.7%
O	12965	9.1%
A	11118	7.8%
M	11118	7.8%
W	1785	1.3%
H	62	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	142745	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
T	23214	16.3%
E	23214	16.3%
R	23214	16.3%
G	22236	15.6%
N	13819	9.7%
O	12965	9.1%
A	11118	7.8%
M	11118	7.8%
W	1785	1.3%
H	62	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	142745	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
T	23214	16.3%
E	23214	16.3%
R	23214	16.3%
G	22236	15.6%
N	13819	9.7%
O	12965	9.1%
A	11118	7.8%
M	11118	7.8%
W	1785	1.3%
H	62	< 0.1%

annual_inc
Real number (ℝ_≥0)

SKEWED

Distinct	3624
Distinct (%)	14.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	69941.35235

Minimum	4080
Maximum	6000000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	4080
5-th percentile	24996
Q1	42000
median	60000
Q3	84000
95-th percentile	142000
Maximum	6000000
Range	5995920
Interquartile range (IQR)	42000

Descriptive statistics

Standard deviation	69394.10716
Coefficient of variation (CV)	0.9921756561
Kurtosis	2591.622465
Mean	69941.35235
Median Absolute Deviation (MAD)	20000
Skewness	36.3657122
Sum	1748463867
Variance	4815542108
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
60000	923	3.7%
50000	682	2.7%
45000	559	2.2%
40000	543	2.2%
75000	521	2.1%
65000	517	2.1%
30000	497	2.0%
70000	482	1.9%
48000	450	1.8%
80000	437	1.7%
Other values (3614)	19388	77.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
4080	1	< 0.1%
4200	1	< 0.1%
4800	1	< 0.1%
5500	1	< 0.1%
6000	3	< 0.1%
7200	2	< 0.1%
8000	3	< 0.1%
8004	1	< 0.1%
8472	1	< 0.1%
9600	15	0.1%

Value	Count	Frequency (%)
6000000	1	< 0.1%
3900000	1	< 0.1%
2039784	1	< 0.1%
1900000	1	< 0.1%
1782000	1	< 0.1%
1440000	1	< 0.1%
1362000	1	< 0.1%
1200000	2	< 0.1%
1176000	1	< 0.1%
948000	1	< 0.1%

verification_status
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	195.4 KiB

Not Verified	10762
Verified	7886
Source Verified	6351

Length

Max length	15
Median length	12
Mean length	11.50034001
Min length	8

Characters and Unicode

Total characters	287497
Distinct characters	13
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Source Verified
2nd row	Not Verified
3rd row	Not Verified
4th row	Verified
5th row	Not Verified

Common Values

Value	Count	Frequency (%)
Not Verified	10762	43.0%
Verified	7886	31.5%
Source Verified	6351	25.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
verified	24999	59.4%
not	10762	25.6%
source	6351	15.1%

Most occurring characters

Value	Count	Frequency (%)
e	56349	19.6%
i	49998	17.4%
r	31350	10.9%
d	24999	8.7%
f	24999	8.7%
V	24999	8.7%
	17113	6.0%
o	17113	6.0%
t	10762	3.7%
N	10762	3.7%
Other values (3)	19053	6.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	228272	79.4%
Uppercase Letter	42112	14.6%
Space Separator	17113	6.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	56349	24.7%
i	49998	21.9%
r	31350	13.7%
d	24999	11.0%
f	24999	11.0%
o	17113	7.5%
t	10762	4.7%
c	6351	2.8%
u	6351	2.8%

Uppercase Letter

Value	Count	Frequency (%)
V	24999	59.4%
N	10762	25.6%
S	6351	15.1%

Space Separator

Value	Count	Frequency (%)
	17113	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	270384	94.0%
Common	17113	6.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	56349	20.8%
i	49998	18.5%
r	31350	11.6%
d	24999	9.2%
f	24999	9.2%
V	24999	9.2%
o	17113	6.3%
t	10762	4.0%
N	10762	4.0%
c	6351	2.3%
Other values (2)	12702	4.7%

Common

Value	Count	Frequency (%)
	17113	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	287497	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	56349	19.6%
i	49998	17.4%
r	31350	10.9%
d	24999	8.7%
f	24999	8.7%
V	24999	8.7%
	17113	6.0%
o	17113	6.0%
t	10762	3.7%
N	10762	3.7%
Other values (3)	19053	6.6%

issue_d
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct	55
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	195.4 KiB

11-Dec	1426
11-Nov	1347
11-Sep	1324
11-Oct	1284
11-Aug	1215
Other values (50)	18403

Length

Max length	6
Median length	6
Mean length	5.836033441
Min length	5

Characters and Unicode

Total characters	145895
Distinct characters	28
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	10-Sep
2nd row	10-Jan
3rd row	9-Oct
4th row	11-Nov
5th row	11-Jul

Common Values

Value	Count	Frequency (%)
11-Dec	1426	5.7%
11-Nov	1347	5.4%
11-Sep	1324	5.3%
11-Oct	1284	5.1%
11-Aug	1215	4.9%
11-Jul	1175	4.7%
11-Jun	1160	4.6%
11-May	1051	4.2%
11-Apr	1008	4.0%
11-Mar	931	3.7%
Other values (45)	13078	52.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
11-dec	1426	5.7%
11-nov	1347	5.4%
11-sep	1324	5.3%
11-oct	1284	5.1%
11-aug	1215	4.9%
11-jul	1175	4.7%
11-jun	1160	4.6%
11-may	1051	4.2%
11-apr	1008	4.0%
11-mar	931	3.7%
Other values (45)	13078	52.3%

Most occurring characters

Value	Count	Frequency (%)
1	34508	23.7%
-	24999	17.1%
0	7292	5.0%
e	6549	4.5%
u	6536	4.5%
J	5784	4.0%
c	5203	3.6%
a	5111	3.5%
p	4108	2.8%
A	4040	2.8%
Other values (18)	41765	28.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	49998	34.3%
Decimal Number	45899	31.5%
Dash Punctuation	24999	17.1%
Uppercase Letter	24999	17.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	6549	13.1%
u	6536	13.1%
c	5203	10.4%
a	5111	10.2%
p	4108	8.2%
n	3580	7.2%
r	3531	7.1%
v	2584	5.2%
o	2584	5.2%
t	2430	4.9%
Other values (4)	7782	15.6%

Uppercase Letter

Value	Count	Frequency (%)
J	5784	23.1%
A	4040	16.2%
M	3612	14.4%
D	2773	11.1%
N	2584	10.3%
O	2430	9.7%
S	2319	9.3%
F	1457	5.8%

Decimal Number

Value	Count	Frequency (%)
1	34508	75.2%
0	7292	15.9%
9	2996	6.5%
8	953	2.1%
7	150	0.3%

Dash Punctuation

Value	Count	Frequency (%)
-	24999	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	74997	51.4%
Common	70898	48.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	6549	8.7%
u	6536	8.7%
J	5784	7.7%
c	5203	6.9%
a	5111	6.8%
p	4108	5.5%
A	4040	5.4%
M	3612	4.8%
n	3580	4.8%
r	3531	4.7%
Other values (12)	26943	35.9%

Common

Value	Count	Frequency (%)
1	34508	48.7%
-	24999	35.3%
0	7292	10.3%
9	2996	4.2%
8	953	1.3%
7	150	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	145895	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	34508	23.7%
-	24999	17.1%
0	7292	5.0%
e	6549	4.5%
u	6536	4.5%
J	5784	4.0%
c	5203	3.6%
a	5111	3.5%
p	4108	2.8%
A	4040	2.8%
Other values (18)	41765	28.6%

loan_status
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	195.4 KiB

Fully Paid	20827
Charged Off	3474
Current	698

Length

Max length	11
Median length	10
Mean length	10.05520221
Min length	7

Characters and Unicode

Total characters	251370
Distinct characters	18
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Charged Off
2nd row	Fully Paid
3rd row	Fully Paid
4th row	Current
5th row	Fully Paid

Common Values

Value	Count	Frequency (%)
Fully Paid	20827	83.3%
Charged Off	3474	13.9%
Current	698	2.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
paid	20827	42.2%
fully	20827	42.2%
off	3474	7.0%
charged	3474	7.0%
current	698	1.4%

Most occurring characters

Value	Count	Frequency (%)
l	41654	16.6%
d	24301	9.7%
	24301	9.7%
a	24301	9.7%
u	21525	8.6%
i	20827	8.3%
y	20827	8.3%
P	20827	8.3%
F	20827	8.3%
f	6948	2.8%
Other values (8)	25032	10.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	177769	70.7%
Uppercase Letter	49300	19.6%
Space Separator	24301	9.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
l	41654	23.4%
d	24301	13.7%
a	24301	13.7%
u	21525	12.1%
i	20827	11.7%
y	20827	11.7%
f	6948	3.9%
r	4870	2.7%
e	4172	2.3%
h	3474	2.0%
Other values (3)	4870	2.7%

Uppercase Letter

Value	Count	Frequency (%)
P	20827	42.2%
F	20827	42.2%
C	4172	8.5%
O	3474	7.0%

Space Separator

Value	Count	Frequency (%)
	24301	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	227069	90.3%
Common	24301	9.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
l	41654	18.3%
d	24301	10.7%
a	24301	10.7%
u	21525	9.5%
i	20827	9.2%
y	20827	9.2%
P	20827	9.2%
F	20827	9.2%
f	6948	3.1%
r	4870	2.1%
Other values (7)	20162	8.9%

Common

Value	Count	Frequency (%)
	24301	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	251370	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
l	41654	16.6%
d	24301	9.7%
	24301	9.7%
a	24301	9.7%
u	21525	8.6%
i	20827	8.3%
y	20827	8.3%
P	20827	8.3%
F	20827	8.3%
f	6948	2.8%
Other values (8)	25032	10.0%

desc
Categorical

HIGH CARDINALITY
MISSING

Distinct	16661
Distinct (%)	99.1%
Missing	8192
Missing (%)	32.8%
Memory size	195.4 KiB

	135
Debt Consolidation	4
refinancing	2
credit card debt consolidation	2
debt consolidation	2
Other values (16656)	16662

Length

Max length	3976
Median length	288
Mean length	427.4410067
Min length	1

Characters and Unicode

Total characters	7184001
Distinct characters	139
Distinct categories	17 ?
Distinct scripts	2 ?
Distinct blocks	4 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	16650 ?
Unique (%)	99.1%

Sample

1st row	Borrower added on 08/30/10 > thank you<br/>
2nd row	Borrower added on 01/14/10 > Green city housing project<br/> Borrower added on 01/23/10 > I mistyped in the application. $1400 is the current rent we pay. <br/><br/>My employer is Emerson, and my role is marketing and biz dev director. Been with them for 3 years now. My 2009 annual compensation was ~160K. <br/><br/>I have zero credit card debt or car loans. Purpose of the loan is to buy real estate in my home town in India. It costs ~$140K. Rather than taking a mortgage there, I want to buy the property outright. I used $125K from my savings, and I am short $15K. The name of the building community is Green City - www.vplprojects.com.<br/>
3rd row
4th row	Borrower added on 11/10/11 > Consolidate all debt. On Job 27 years. Loan payment is less than 7%<br>of monthly income.<br>
5th row	Borrower added on 06/29/11 > thanks for the help.<br/>

Common Values

Value	Count	Frequency (%)
	135	0.5%
Debt Consolidation	4	< 0.1%
refinancing	2	< 0.1%
credit card debt consolidation	2	< 0.1%
debt consolidation	2	< 0.1%
Borrower added on 09/21/11 > Debt consolidation<br/>	2	< 0.1%
Camping Membership	2	< 0.1%
Motorcycle Loan	2	< 0.1%
I have 2nd mortgage on a rental property with balance of $109k. I have cash flow of $85k and plan to pay off the 2nd mortgage using this loan to make up for rest of the balance. You will see a 2nd mortgage debt on my credit around $965.00 which will go away once this loan is approved as I will be paying it off. The interest rate needs to be below 9% since I can use my credit card to borrow same money for 10%.	2	< 0.1%
Personal loan	2	< 0.1%
Other values (16651)	16652	66.6%
(Missing)	8192	32.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
i	49098	3.8%
to	44997	3.5%
a	34523	2.7%
the	34233	2.6%
and	34201	2.6%
my	32571	2.5%
on	30685	2.4%
	23195	1.8%
for	20766	1.6%
have	20552	1.6%
Other values (39405)	967193	74.9%

Most occurring characters

Value	Count	Frequency (%)
	1334899	18.6%
e	599750	8.3%
a	450037	6.3%
o	446547	6.2%
t	409799	5.7%
n	385304	5.4%
r	370053	5.2%
i	312061	4.3%
s	267670	3.7%
d	250709	3.5%
Other values (129)	2357172	32.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	5124065	71.3%
Space Separator	1334940	18.6%
Decimal Number	216787	3.0%
Other Punctuation	204469	2.8%
Uppercase Letter	186131	2.6%
Math Symbol	88051	1.2%
Currency Symbol	10454	0.1%
Dash Punctuation	8460	0.1%
Close Punctuation	4658	0.1%
Open Punctuation	4253	0.1%
Other values (7)	1733	< 0.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
I	59562	32.0%
B	21669	11.6%
T	17603	9.5%
A	9391	5.0%
M	8824	4.7%
C	8772	4.7%
S	5632	3.0%
W	5415	2.9%
L	5372	2.9%
E	5348	2.9%
Other values (21)	38543	20.7%

Lowercase Letter

Value	Count	Frequency (%)
e	599750	11.7%
a	450037	8.8%
o	446547	8.7%
t	409799	8.0%
n	385304	7.5%
r	370053	7.2%
i	312061	6.1%
s	267670	5.2%
d	250709	4.9%
l	224257	4.4%
Other values (17)	1407878	27.5%

Other Punctuation

Value	Count	Frequency (%)
.	75646	37.0%
/	72751	35.6%
,	31154	15.2%
'	8354	4.1%
!	4335	2.1%
%	3542	1.7%
:	3351	1.6%
;	2124	1.0%
&	1658	0.8%
"	504	0.2%
Other values (10)	1050	0.5%

Control

Value	Count	Frequency (%)
	770	54.3%
	321	22.6%
	147	10.4%
	31	2.2%
	29	2.0%
	25	1.8%
	25	1.8%
	21	1.5%
	18	1.3%
	13	0.9%
Other values (7)	19	1.3%

Decimal Number

Value	Count	Frequency (%)
0	64982	30.0%
1	61121	28.2%
2	22870	10.5%
5	13545	6.2%
3	11240	5.2%
9	10266	4.7%
4	8440	3.9%
6	8144	3.8%
7	8103	3.7%
8	8076	3.7%

Math Symbol

Value	Count	Frequency (%)
>	53089	60.3%
<	33726	38.3%
+	638	0.7%
=	371	0.4%
~	197	0.2%
¬	25	< 0.1%
\|	5	< 0.1%

Other Symbol

Value	Count	Frequency (%)
¦	95	88.8%
©	9	8.4%
®	2	1.9%
�	1	0.9%

Dash Punctuation

Value	Count	Frequency (%)
-	8447	99.8%
—	9	0.1%
–	4	< 0.1%

Close Punctuation

Value	Count	Frequency (%)
)	4636	99.5%
]	19	0.4%
}	3	0.1%

Open Punctuation

Value	Count	Frequency (%)
(	4233	99.5%
[	18	0.4%
{	2	< 0.1%

Modifier Symbol

Value	Count	Frequency (%)
`	8	66.7%
^	3	25.0%
¯	1	8.3%

Space Separator

Value	Count	Frequency (%)
	1334899	> 99.9%
	41	< 0.1%

Currency Symbol

Value	Count	Frequency (%)
$	10408	99.6%
¢	46	0.4%

Final Punctuation

Value	Count	Frequency (%)
’	53	84.1%
”	10	15.9%

Initial Punctuation

Value	Count	Frequency (%)
“	10	90.9%
‘	1	9.1%

Other Number

Value	Count	Frequency (%)
½	5	71.4%
¾	2	28.6%

Connector Punctuation

Value	Count	Frequency (%)
_	114	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	5310196	73.9%
Common	1873805	26.1%

Most frequent character per script

Common

Value	Count	Frequency (%)
	1334899	71.2%
.	75646	4.0%
/	72751	3.9%
0	64982	3.5%
1	61121	3.3%
>	53089	2.8%
<	33726	1.8%
,	31154	1.7%
2	22870	1.2%
5	13545	0.7%
Other values (71)	110022	5.9%

Latin

Value	Count	Frequency (%)
e	599750	11.3%
a	450037	8.5%
o	446547	8.4%
t	409799	7.7%
n	385304	7.3%
r	370053	7.0%
i	312061	5.9%
s	267670	5.0%
d	250709	4.7%
l	224257	4.2%
Other values (48)	1594009	30.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	7182483	> 99.9%
None	1414	< 0.1%
Punctuation	103	< 0.1%
Specials	1	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	1334899	18.6%
e	599750	8.4%
a	450037	6.3%
o	446547	6.2%
t	409799	5.7%
n	385304	5.4%
r	370053	5.2%
i	312061	4.3%
s	267670	3.7%
d	250709	3.5%
Other values (86)	2355654	32.8%

None

Value	Count	Frequency (%)
â	342	24.2%
	321	22.7%
	147	10.4%
¦	95	6.7%
Â	87	6.2%
Ã	81	5.7%
¢	46	3.3%
	41	2.9%
	31	2.2%
	29	2.1%
Other values (24)	194	13.7%

Punctuation

Value	Count	Frequency (%)
’	53	51.5%
“	10	9.7%
”	10	9.7%
—	9	8.7%
…	8	7.8%
•	8	7.8%
–	4	3.9%
‘	1	1.0%

Specials

Value	Count	Frequency (%)
�	1	100.0%

purpose
Categorical

Distinct	14
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	195.4 KiB

debt_consolidation	11932
credit_card	3246
other	2475
home_improvement	1883
major_purchase	1370
Other values (9)	4093

Length

Max length	18
Median length	16
Mean length	13.78079123
Min length	3

Characters and Unicode

Total characters	344506
Distinct characters	22
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	home_improvement
2nd row	other
3rd row	major_purchase
4th row	debt_consolidation
5th row	debt_consolidation

Common Values

Value	Count	Frequency (%)
debt_consolidation	11932	47.7%
credit_card	3246	13.0%
other	2475	9.9%
home_improvement	1883	7.5%
major_purchase	1370	5.5%
car	992	4.0%
small_business	975	3.9%
wedding	613	2.5%
medical	434	1.7%
moving	346	1.4%
Other values (4)	733	2.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
debt_consolidation	11932	47.7%
credit_card	3246	13.0%
other	2475	9.9%
home_improvement	1883	7.5%
major_purchase	1370	5.5%
car	992	4.0%
small_business	975	3.9%
wedding	613	2.5%
medical	434	1.7%
moving	346	1.4%
Other values (4)	733	2.9%

Most occurring characters

Value	Count	Frequency (%)
o	44425	12.9%
d	32227	9.4%
t	31915	9.3%
i	31808	9.2%
n	28250	8.2%
e	27435	8.0%
c	21667	6.3%
a	21274	6.2%
_	19467	5.7%
s	17427	5.1%
Other values (12)	68611	19.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	325039	94.3%
Connector Punctuation	19467	5.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	44425	13.7%
d	32227	9.9%
t	31915	9.8%
i	31808	9.8%
n	28250	8.7%
e	27435	8.4%
c	21667	6.7%
a	21274	6.5%
s	17427	5.4%
r	14704	4.5%
Other values (11)	53907	16.6%

Connector Punctuation

Value	Count	Frequency (%)
_	19467	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	325039	94.3%
Common	19467	5.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	44425	13.7%
d	32227	9.9%
t	31915	9.8%
i	31808	9.8%
n	28250	8.7%
e	27435	8.4%
c	21667	6.7%
a	21274	6.5%
s	17427	5.4%
r	14704	4.5%
Other values (11)	53907	16.6%

Common

Value	Count	Frequency (%)
_	19467	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	344506	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	44425	12.9%
d	32227	9.4%
t	31915	9.3%
i	31808	9.2%
n	28250	8.2%
e	27435	8.0%
c	21667	6.3%
a	21274	6.2%
_	19467	5.7%
s	17427	5.1%
Other values (12)	68611	19.9%

title
Categorical

HIGH CARDINALITY

Distinct	12893
Distinct (%)	51.6%
Missing	8
Missing (%)	< 0.1%
Memory size	195.4 KiB

Debt Consolidation	1407
Debt Consolidation Loan	1092
Personal Loan	439
Consolidation	345
debt consolidation	314
Other values (12888)	21394

Length

Max length	80
Median length	16
Mean length	17.24488816
Min length	1

Characters and Unicode

Total characters	430967
Distinct characters	100
Distinct categories	15 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	11604 ?
Unique (%)	46.4%

Sample

1st row	homeimproement
2nd row	Green City
3rd row	payoff w/in 2 years
4th row	Loan I
5th row	save %

Common Values

Value	Count	Frequency (%)
Debt Consolidation	1407	5.6%
Debt Consolidation Loan	1092	4.4%
Personal Loan	439	1.8%
Consolidation	345	1.4%
debt consolidation	314	1.3%
Home Improvement	233	0.9%
Debt consolidation	227	0.9%
Credit Card Consolidation	223	0.9%
Credit Card Loan	196	0.8%
Personal	192	0.8%
Other values (12883)	20323	81.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
loan	6903	10.5%
debt	5906	9.0%
consolidation	5550	8.4%
credit	2958	4.5%
card	2145	3.3%
personal	1352	2.1%
home	1194	1.8%
pay	864	1.3%
off	811	1.2%
my	732	1.1%
Other values (6455)	37509	56.9%

Most occurring characters

Value	Count	Frequency (%)
o	41839	9.7%
	41691	9.7%
n	35314	8.2%
e	34200	7.9%
a	31873	7.4%
i	27832	6.5%
t	26951	6.3%
d	19611	4.6%
r	18341	4.3%
s	17814	4.1%
Other values (90)	135501	31.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	329371	76.4%
Uppercase Letter	52216	12.1%
Space Separator	41691	9.7%
Decimal Number	3959	0.9%
Other Punctuation	2840	0.7%
Dash Punctuation	508	0.1%
Connector Punctuation	128	< 0.1%
Close Punctuation	66	< 0.1%
Currency Symbol	64	< 0.1%
Math Symbol	58	< 0.1%
Other values (5)	66	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	41839	12.7%
n	35314	10.7%
e	34200	10.4%
a	31873	9.7%
i	27832	8.5%
t	26951	8.2%
d	19611	6.0%
r	18341	5.6%
s	17814	5.4%
l	16575	5.0%
Other values (17)	59021	17.9%

Uppercase Letter

Value	Count	Frequency (%)
C	11801	22.6%
L	6522	12.5%
D	5873	11.2%
P	3583	6.9%
R	2389	4.6%
M	1965	3.8%
S	1918	3.7%
B	1885	3.6%
E	1798	3.4%
I	1790	3.4%
Other values (17)	12692	24.3%

Other Punctuation

Value	Count	Frequency (%)
!	710	25.0%
'	638	22.5%
.	450	15.8%
/	359	12.6%
,	273	9.6%
&	204	7.2%
%	56	2.0%
:	38	1.3%
"	35	1.2%
*	22	0.8%
Other values (5)	55	1.9%

Decimal Number

Value	Count	Frequency (%)
1	1130	28.5%
0	1112	28.1%
2	713	18.0%
3	201	5.1%
5	172	4.3%
9	166	4.2%
4	153	3.9%
6	114	2.9%
8	109	2.8%
7	89	2.2%

Math Symbol

Value	Count	Frequency (%)
+	30	51.7%
=	12	20.7%
<	9	15.5%
>	6	10.3%
~	1	1.7%

Control

Value	Count	Frequency (%)
	4	44.4%
	2	22.2%
	2	22.2%
	1	11.1%

Close Punctuation

Value	Count	Frequency (%)
)	64	97.0%
]	2	3.0%

Open Punctuation

Value	Count	Frequency (%)
(	50	96.2%
[	2	3.8%

Modifier Symbol

Value	Count	Frequency (%)
^	1	50.0%
`	1	50.0%

Space Separator

Value	Count	Frequency (%)
	41691	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	508	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	128	100.0%

Currency Symbol

Value	Count	Frequency (%)
$	64	100.0%

Other Symbol

Value	Count	Frequency (%)
¦	2	100.0%

Other Number

Value	Count	Frequency (%)
³	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	381587	88.5%
Common	49380	11.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	41839	11.0%
n	35314	9.3%
e	34200	9.0%
a	31873	8.4%
i	27832	7.3%
t	26951	7.1%
d	19611	5.1%
r	18341	4.8%
s	17814	4.7%
l	16575	4.3%
Other values (44)	111237	29.2%

Common

Value	Count	Frequency (%)
	41691	84.4%
1	1130	2.3%
0	1112	2.3%
2	713	1.4%
!	710	1.4%
'	638	1.3%
-	508	1.0%
.	450	0.9%
/	359	0.7%
,	273	0.6%
Other values (36)	1796	3.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	430952	> 99.9%
None	15	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	41839	9.7%
	41691	9.7%
n	35314	8.2%
e	34200	7.9%
a	31873	7.4%
i	27832	6.5%
t	26951	6.3%
d	19611	4.6%
r	18341	4.3%
s	17814	4.1%
Other values (83)	135486	31.4%

None

Value	Count	Frequency (%)
â	4	26.7%
	4	26.7%
	2	13.3%
¦	2	13.3%
	1	6.7%
Ã	1	6.7%
³	1	6.7%

zip_code
Categorical

HIGH CARDINALITY

Distinct	787
Distinct (%)	3.1%
Missing	0
Missing (%)	0.0%
Memory size	195.4 KiB

100xx	409
112xx	379
945xx	351
606xx	346
070xx	312
Other values (782)	23202

Length

Max length	5
Median length	5
Mean length	5
Min length	5

Characters and Unicode

Total characters	124995
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	62 ?
Unique (%)	0.2%

Sample

1st row	076xx
2nd row	300xx
3rd row	310xx
4th row	488xx
5th row	334xx

Common Values

Value	Count	Frequency (%)
100xx	409	1.6%
112xx	379	1.5%
945xx	351	1.4%
606xx	346	1.4%
070xx	312	1.2%
900xx	294	1.2%
021xx	262	1.0%
300xx	254	1.0%
750xx	252	1.0%
331xx	249	1.0%
Other values (777)	21891	87.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
100xx	409	1.6%
112xx	379	1.5%
945xx	351	1.4%
606xx	346	1.4%
070xx	312	1.2%
900xx	294	1.2%
021xx	262	1.0%
300xx	254	1.0%
750xx	252	1.0%
331xx	249	1.0%
Other values (777)	21891	87.6%

Most occurring characters

Value	Count	Frequency (%)
x	49998	40.0%
0	12744	10.2%
1	10282	8.2%
2	8577	6.9%
3	7743	6.2%
9	7716	6.2%
7	6454	5.2%
4	5761	4.6%
5	5457	4.4%
8	5324	4.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	74997	60.0%
Lowercase Letter	49998	40.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	12744	17.0%
1	10282	13.7%
2	8577	11.4%
3	7743	10.3%
9	7716	10.3%
7	6454	8.6%
4	5761	7.7%
5	5457	7.3%
8	5324	7.1%
6	4939	6.6%

Lowercase Letter

Value	Count	Frequency (%)
x	49998	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	74997	60.0%
Latin	49998	40.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	12744	17.0%
1	10282	13.7%
2	8577	11.4%
3	7743	10.3%
9	7716	10.3%
7	6454	8.6%
4	5761	7.7%
5	5457	7.3%
8	5324	7.1%
6	4939	6.6%

Latin

Value	Count	Frequency (%)
x	49998	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	124995	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
x	49998	40.0%
0	12744	10.2%
1	10282	8.2%
2	8577	6.9%
3	7743	6.2%
9	7716	6.2%
7	6454	5.2%
4	5761	4.6%
5	5457	4.4%
8	5324	4.3%

addr_state
Categorical

Distinct	50
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	195.4 KiB

CA	4414
NY	2616
FL	1801
TX	1693
NJ	1217
Other values (45)	13258

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	49998
Distinct characters	24
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	NJ
2nd row	GA
3rd row	GA
4th row	MI
5th row	FL

Common Values

Value	Count	Frequency (%)
CA	4414	17.7%
NY	2616	10.5%
FL	1801	7.2%
TX	1693	6.8%
NJ	1217	4.9%
IL	1040	4.2%
PA	978	3.9%
GA	862	3.4%
MA	852	3.4%
VA	848	3.4%
Other values (40)	8678	34.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
ca	4414	17.7%
ny	2616	10.5%
fl	1801	7.2%
tx	1693	6.8%
nj	1217	4.9%
il	1040	4.2%
pa	978	3.9%
ga	862	3.4%
ma	852	3.4%
va	848	3.4%
Other values (40)	8678	34.7%

Most occurring characters

Value	Count	Frequency (%)
A	9706	19.4%
C	6247	12.5%
N	5232	10.5%
L	3382	6.8%
M	2970	5.9%
Y	2867	5.7%
T	2357	4.7%
O	2151	4.3%
I	2030	4.1%
F	1801	3.6%
Other values (14)	11255	22.5%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	49998	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	9706	19.4%
C	6247	12.5%
N	5232	10.5%
L	3382	6.8%
M	2970	5.9%
Y	2867	5.7%
T	2357	4.7%
O	2151	4.3%
I	2030	4.1%
F	1801	3.6%
Other values (14)	11255	22.5%

Most occurring scripts

Value	Count	Frequency (%)
Latin	49998	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	9706	19.4%
C	6247	12.5%
N	5232	10.5%
L	3382	6.8%
M	2970	5.9%
Y	2867	5.7%
T	2357	4.7%
O	2151	4.3%
I	2030	4.1%
F	1801	3.6%
Other values (14)	11255	22.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	49998	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	9706	19.4%
C	6247	12.5%
N	5232	10.5%
L	3382	6.8%
M	2970	5.9%
Y	2867	5.7%
T	2357	4.7%
O	2151	4.3%
I	2030	4.1%
F	1801	3.6%
Other values (14)	11255	22.5%

dti
Real number (ℝ_≥0)

Distinct	2779
Distinct (%)	11.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	13.33020961

Minimum	0
Maximum	29.99
Zeros	115
Zeros (%)	0.5%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	0
5-th percentile	2.18
Q1	8.22
median	13.42
Q3	18.57
95-th percentile	23.82
Maximum	29.99
Range	29.99
Interquartile range (IQR)	10.35

Descriptive statistics

Standard deviation	6.651601507
Coefficient of variation (CV)	0.4989870154
Kurtosis	-0.8462498933
Mean	13.33020961
Median Absolute Deviation (MAD)	5.17
Skewness	-0.03000580225
Sum	333241.91
Variance	44.24380261
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	115	0.5%
12	30	0.1%
12.48	30	0.1%
18	28	0.1%
9.6	27	0.1%
19.2	27	0.1%
17.04	26	0.1%
12.15	23	0.1%
10.64	23	0.1%
13.5	23	0.1%
Other values (2769)	24647	98.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	115	0.5%
0.01	2	< 0.1%
0.02	3	< 0.1%
0.04	3	< 0.1%
0.05	1	< 0.1%
0.07	2	< 0.1%
0.08	2	< 0.1%
0.09	3	< 0.1%
0.12	1	< 0.1%
0.13	6	< 0.1%

Value	Count	Frequency (%)
29.99	1	< 0.1%
29.95	1	< 0.1%
29.93	1	< 0.1%
29.92	1	< 0.1%
29.86	1	< 0.1%
29.85	1	< 0.1%
29.82	1	< 0.1%
29.79	1	< 0.1%
29.78	1	< 0.1%
29.76	1	< 0.1%

delinq_2yrs
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	11
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.1454058162

Minimum	0
Maximum	11
Zeros	22317
Zeros (%)	89.3%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	1
Maximum	11
Range	11
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.494810652
Coefficient of variation (CV)	3.402963271
Kurtosis	45.48428249
Mean	0.1454058162
Median Absolute Deviation (MAD)	0
Skewness	5.282407091
Sum	3635
Variance	0.2448375813
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
0	22317	89.3%
1	2054	8.2%
2	420	1.7%
3	144	0.6%
4	39	0.2%
5	13	0.1%
7	4	< 0.1%
6	4	< 0.1%
8	2	< 0.1%
11	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	22317	89.3%
1	2054	8.2%
2	420	1.7%
3	144	0.6%
4	39	0.2%
5	13	0.1%
6	4	< 0.1%
7	4	< 0.1%
8	2	< 0.1%
9	1	< 0.1%

Value	Count	Frequency (%)
11	1	< 0.1%
9	1	< 0.1%
8	2	< 0.1%
7	4	< 0.1%
6	4	< 0.1%
5	13	0.1%
4	39	0.2%
3	144	0.6%
2	420	1.7%
1	2054	8.2%

earliest_cr_line
Categorical

HIGH CARDINALITY

Distinct	495
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	195.4 KiB

Nov-98	246
Oct-99	233
Dec-98	232
Oct-00	211
Nov-99	208
Other values (490)	23869

Length

Max length	6
Median length	6
Mean length	5.703868155
Min length	5

Characters and Unicode

Total characters	142591
Distinct characters	33
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	46 ?
Unique (%)	0.2%

Sample

1st row	1-Feb
2nd row	Feb-97
3rd row	Mar-00
4th row	Jun-99
5th row	4-Jun

Common Values

Value	Count	Frequency (%)
Nov-98	246	1.0%
Oct-99	233	0.9%
Dec-98	232	0.9%
Oct-00	211	0.8%
Nov-99	208	0.8%
Dec-99	207	0.8%
Nov-97	207	0.8%
Nov-00	203	0.8%
Dec-97	200	0.8%
Sep-00	199	0.8%
Other values (485)	22853	91.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
nov-98	246	1.0%
oct-99	233	0.9%
dec-98	232	0.9%
oct-00	211	0.8%
nov-99	208	0.8%
dec-99	207	0.8%
nov-97	207	0.8%
nov-00	203	0.8%
dec-97	200	0.8%
sep-00	199	0.8%
Other values (485)	22853	91.4%

Most occurring characters

Value	Count	Frequency (%)
-	24999	17.5%
9	14807	10.4%
e	6632	4.7%
J	5870	4.1%
u	5847	4.1%
a	5742	4.0%
8	5223	3.7%
c	5121	3.6%
0	4924	3.5%
p	3945	2.8%
Other values (23)	59481	41.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	49998	35.1%
Decimal Number	42595	29.9%
Dash Punctuation	24999	17.5%
Uppercase Letter	24999	17.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	6632	13.3%
u	5847	11.7%
a	5742	11.5%
c	5121	10.2%
p	3945	7.9%
n	3930	7.9%
r	3444	6.9%
t	2565	5.1%
v	2525	5.1%
o	2525	5.1%
Other values (4)	7722	15.4%

Decimal Number

Value	Count	Frequency (%)
9	14807	34.8%
8	5223	12.3%
0	4924	11.6%
7	2985	7.0%
4	2690	6.3%
5	2597	6.1%
6	2544	6.0%
1	2390	5.6%
3	2351	5.5%
2	2084	4.9%

Uppercase Letter

Value	Count	Frequency (%)
J	5870	23.5%
A	3809	15.2%
M	3598	14.4%
O	2565	10.3%
D	2556	10.2%
N	2525	10.1%
S	2257	9.0%
F	1819	7.3%

Dash Punctuation

Value	Count	Frequency (%)
-	24999	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	74997	52.6%
Common	67594	47.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	6632	8.8%
J	5870	7.8%
u	5847	7.8%
a	5742	7.7%
c	5121	6.8%
p	3945	5.3%
n	3930	5.2%
A	3809	5.1%
M	3598	4.8%
r	3444	4.6%
Other values (12)	27059	36.1%

Common

Value	Count	Frequency (%)
-	24999	37.0%
9	14807	21.9%
8	5223	7.7%
0	4924	7.3%
7	2985	4.4%
4	2690	4.0%
5	2597	3.8%
6	2544	3.8%
1	2390	3.5%
3	2351	3.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	142591	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
-	24999	17.5%
9	14807	10.4%
e	6632	4.7%
J	5870	4.1%
u	5847	4.1%
a	5742	4.0%
8	5223	3.7%
c	5121	3.6%
0	4924	3.5%
p	3945	2.8%
Other values (23)	59481	41.7%

inq_last_6mths
Real number (ℝ_≥0)

ZEROS

Distinct	9
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.8686347454

Minimum	0
Maximum	8
Zeros	12185
Zeros (%)	48.7%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	1
95-th percentile	3
Maximum	8
Range	8
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.070605229
Coefficient of variation (CV)	1.232514857
Kurtosis	2.586075043
Mean	0.8686347454
Median Absolute Deviation (MAD)	1
Skewness	1.388853666
Sum	21715
Variance	1.146195556
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
0	12185	48.7%
1	6830	27.3%
2	3709	14.8%
3	1904	7.6%
4	214	0.9%
5	87	0.3%
6	37	0.1%
7	22	0.1%
8	11	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	12185	48.7%
1	6830	27.3%
2	3709	14.8%
3	1904	7.6%
4	214	0.9%
5	87	0.3%
6	37	0.1%
7	22	0.1%
8	11	< 0.1%

Value	Count	Frequency (%)
8	11	< 0.1%
7	22	0.1%
6	37	0.1%
5	87	0.3%
4	214	0.9%
3	1904	7.6%
2	3709	14.8%
1	6830	27.3%
0	12185	48.7%

mths_since_last_delinq
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct	91
Distinct (%)	1.0%
Missing	16240
Missing (%)	65.0%
Infinite	0
Infinite (%)	0.0%
Mean	35.90980706

Minimum	0
Maximum	120
Zeros	260
Zeros (%)	1.0%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	0
5-th percentile	3
Q1	18
median	34
Q3	52
95-th percentile	75
Maximum	120
Range	120
Interquartile range (IQR)	34

Descriptive statistics

Standard deviation	21.94852379
Coefficient of variation (CV)	0.6112125236
Kurtosis	-0.8194621947
Mean	35.90980706
Median Absolute Deviation (MAD)	16
Skewness	0.3153063033
Sum	314534
Variance	481.7376967
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	260	1.0%
15	160	0.6%
35	157	0.6%
23	154	0.6%
24	154	0.6%
20	153	0.6%
30	153	0.6%
26	151	0.6%
45	149	0.6%
38	146	0.6%
Other values (81)	7122	28.5%
(Missing)	16240	65.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	260	1.0%
1	21	0.1%
2	71	0.3%
3	91	0.4%
4	94	0.4%
5	86	0.3%
6	115	0.5%
7	110	0.4%
8	106	0.4%
9	112	0.4%

Value	Count	Frequency (%)
120	1	< 0.1%
115	1	< 0.1%
103	1	< 0.1%
96	1	< 0.1%
95	1	< 0.1%
86	2	< 0.1%
85	1	< 0.1%
83	4	< 0.1%
82	32	0.1%
81	59	0.2%

mths_since_last_record
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct	104
Distinct (%)	6.2%
Missing	23320
Missing (%)	93.3%
Infinite	0
Infinite (%)	0.0%
Mean	69.73079214

Minimum	0
Maximum	129
Zeros	404
Zeros (%)	1.6%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	21
median	90
Q3	104
95-th percentile	115
Maximum	129
Range	129
Interquartile range (IQR)	83

Descriptive statistics

Standard deviation	43.73019946
Coefficient of variation (CV)	0.6271289643
Kurtosis	-1.142541955
Mean	69.73079214
Median Absolute Deviation (MAD)	20
Skewness	-0.7269989059
Sum	117078
Variance	1912.330344
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	404	1.6%
104	42	0.2%
94	40	0.2%
113	40	0.2%
110	35	0.1%
99	35	0.1%
93	35	0.1%
108	34	0.1%
87	34	0.1%
89	34	0.1%
Other values (94)	946	3.8%
(Missing)	23320	93.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	404	1.6%
6	1	< 0.1%
11	1	< 0.1%
12	1	< 0.1%
13	2	< 0.1%
14	1	< 0.1%
17	2	< 0.1%
18	2	< 0.1%
21	7	< 0.1%
22	1	< 0.1%

Value	Count	Frequency (%)
129	1	< 0.1%
119	5	< 0.1%
118	21	0.1%
117	31	0.1%
116	22	0.1%
115	22	0.1%
114	26	0.1%
113	40	0.2%
112	21	0.1%
111	29	0.1%

open_acc
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	38
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	9.360734429

Minimum	2
Maximum	44
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	2
5-th percentile	4
Q1	6
median	9
Q3	12
95-th percentile	18
Maximum	44
Range	42
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	4.394020991
Coefficient of variation (CV)	0.469409855
Kurtosis	1.722384147
Mean	9.360734429
Median Absolute Deviation (MAD)	3
Skewness	1.008470991
Sum	234009
Variance	19.30742047
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=38)

Value	Count	Frequency (%)
7	2561	10.2%
8	2478	9.9%
6	2449	9.8%
9	2385	9.5%
10	2054	8.2%
5	1985	7.9%
11	1724	6.9%
12	1453	5.8%
4	1401	5.6%
13	1227	4.9%
Other values (28)	5282	21.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	350	1.4%
3	890	3.6%
4	1401	5.6%
5	1985	7.9%
6	2449	9.8%
7	2561	10.2%
8	2478	9.9%
9	2385	9.5%
10	2054	8.2%
11	1724	6.9%

Value	Count	Frequency (%)
44	1	< 0.1%
41	1	< 0.1%
39	1	< 0.1%
38	1	< 0.1%
36	1	< 0.1%
34	5	< 0.1%
33	2	< 0.1%
32	2	< 0.1%
31	5	< 0.1%
30	8	< 0.1%

pub_rec
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	195.4 KiB

0	23724
1	1235
2	34
3	4
4	2

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	24999
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	2
5th row	1

Common Values

Value	Count	Frequency (%)
0	23724	94.9%
1	1235	4.9%
2	34	0.1%
3	4	< 0.1%
4	2	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	23724	94.9%
1	1235	4.9%
2	34	0.1%
3	4	< 0.1%
4	2	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	23724	94.9%
1	1235	4.9%
2	34	0.1%
3	4	< 0.1%
4	2	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	24999	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	23724	94.9%
1	1235	4.9%
2	34	0.1%
3	4	< 0.1%
4	2	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	24999	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	23724	94.9%
1	1235	4.9%
2	34	0.1%
3	4	< 0.1%
4	2	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	24999	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	23724	94.9%
1	1235	4.9%
2	34	0.1%
3	4	< 0.1%
4	2	< 0.1%

revol_bal
Real number (ℝ_≥0)

ZEROS

Distinct	16468
Distinct (%)	65.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	13505.54998

Minimum	0
Maximum	149588
Zeros	621
Zeros (%)	2.5%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	0
5-th percentile	353
Q1	3838.5
median	8992
Q3	17249.5
95-th percentile	41957.7
Maximum	149588
Range	149588
Interquartile range (IQR)	13411

Descriptive statistics

Standard deviation	15832.4205
Coefficient of variation (CV)	1.172289949
Kurtosis	14.43225533
Mean	13505.54998
Median Absolute Deviation (MAD)	6062
Skewness	3.13909295
Sum	337625244
Variance	250665538.8
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	621	2.5%
1	9	< 0.1%
23	8	< 0.1%
798	8	< 0.1%
482	7	< 0.1%
52	7	< 0.1%
452	7	< 0.1%
39	7	< 0.1%
2834	6	< 0.1%
1836	6	< 0.1%
Other values (16458)	24313	97.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	621	2.5%
1	9	< 0.1%
2	3	< 0.1%
3	4	< 0.1%
4	3	< 0.1%
5	6	< 0.1%
6	4	< 0.1%
7	1	< 0.1%
8	3	< 0.1%
9	3	< 0.1%

Value	Count	Frequency (%)
149588	1	< 0.1%
148804	1	< 0.1%
147897	1	< 0.1%
147750	1	< 0.1%
147559	1	< 0.1%
147451	1	< 0.1%
146472	1	< 0.1%
145711	1	< 0.1%
145518	1	< 0.1%
145384	1	< 0.1%

revol_util
Categorical

HIGH CARDINALITY

Distinct	1059
Distinct (%)	4.2%
Missing	29
Missing (%)	0.1%
Memory size	195.4 KiB

0%	606
63%	44
66.60%	43
0.20%	43
27.20%	41
Other values (1054)	24193

Length

Max length	6
Median length	6
Mean length	5.528994794
Min length	2

Characters and Unicode

Total characters	138059
Distinct characters	12
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	59 ?
Unique (%)	0.2%

Sample

1st row	1.20%
2nd row	14%
3rd row	34.40%
4th row	91.40%
5th row	9.40%

Common Values

Value	Count	Frequency (%)
0%	606	2.4%
63%	44	0.2%
66.60%	43	0.2%
0.20%	43	0.2%
27.20%	41	0.2%
48.90%	40	0.2%
46.40%	40	0.2%
57.70%	40	0.2%
68.70%	39	0.2%
70.40%	39	0.2%
Other values (1049)	23995	96.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
0	606	2.4%
63	44	0.2%
66.60	43	0.2%
0.20	43	0.2%
27.20	41	0.2%
48.90	40	0.2%
46.40	40	0.2%
57.70	40	0.2%
68.70	39	0.2%
70.40	39	0.2%
Other values (1049)	23995	96.1%

Most occurring characters

Value	Count	Frequency (%)
0	25000	18.1%
%	24970	18.1%
.	21956	15.9%
4	7685	5.6%
7	7607	5.5%
5	7589	5.5%
6	7575	5.5%
3	7515	5.4%
2	7244	5.2%
8	7217	5.2%
Other values (2)	13701	9.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	91133	66.0%
Other Punctuation	46926	34.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	25000	27.4%
4	7685	8.4%
7	7607	8.3%
5	7589	8.3%
6	7575	8.3%
3	7515	8.2%
2	7244	7.9%
8	7217	7.9%
9	6871	7.5%
1	6830	7.5%

Other Punctuation

Value	Count	Frequency (%)
%	24970	53.2%
.	21956	46.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	138059	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	25000	18.1%
%	24970	18.1%
.	21956	15.9%
4	7685	5.6%
7	7607	5.5%
5	7589	5.5%
6	7575	5.5%
3	7515	5.4%
2	7244	5.2%
8	7217	5.2%
Other values (2)	13701	9.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	138059	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	25000	18.1%
%	24970	18.1%
.	21956	15.9%
4	7685	5.6%
7	7607	5.5%
5	7589	5.5%
6	7575	5.5%
3	7515	5.4%
2	7244	5.2%
8	7217	5.2%
Other values (2)	13701	9.9%

total_acc
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	73
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	22.17144686

Minimum	2
Maximum	79
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	2
5-th percentile	7
Q1	14
median	21
Q3	29
95-th percentile	43
Maximum	79
Range	77
Interquartile range (IQR)	15

Descriptive statistics

Standard deviation	11.34068852
Coefficient of variation (CV)	0.5114997046
Kurtosis	0.6481687668
Mean	22.17144686
Median Absolute Deviation (MAD)	8
Skewness	0.8182628719
Sum	554264
Variance	128.611216
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
16	956	3.8%
17	934	3.7%
15	923	3.7%
14	921	3.7%
20	902	3.6%
18	899	3.6%
21	881	3.5%
13	862	3.4%
22	844	3.4%
12	837	3.3%
Other values (63)	16040	64.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	1	< 0.1%
3	96	0.4%
4	255	1.0%
5	335	1.3%
6	415	1.7%
7	518	2.1%
8	619	2.5%
9	681	2.7%
10	712	2.8%
11	767	3.1%

Value	Count	Frequency (%)
79	2	< 0.1%
78	1	< 0.1%
75	2	< 0.1%
73	1	< 0.1%
72	1	< 0.1%
70	1	< 0.1%
69	1	< 0.1%
67	4	< 0.1%
66	4	< 0.1%
65	2	< 0.1%

out_prncp
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	697
Distinct (%)	2.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	48.71904516

Minimum	0
Maximum	6311.47
Zeros	24301
Zeros (%)	97.2%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	6311.47
Range	6311.47
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	366.3814935
Coefficient of variation (CV)	7.520292983
Kurtosis	108.0779983
Mean	48.71904516
Median Absolute Deviation (MAD)	0
Skewness	9.642925645
Sum	1217927.41
Variance	134235.3988
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	24301	97.2%
1972.6	2	< 0.1%
2277.11	2	< 0.1%
233.69	1	< 0.1%
456.16	1	< 0.1%
3106.49	1	< 0.1%
648.56	1	< 0.1%
2833.43	1	< 0.1%
2432.35	1	< 0.1%
1023.3	1	< 0.1%
Other values (687)	687	2.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	24301	97.2%
10.26	1	< 0.1%
13.28	1	< 0.1%
19.12	1	< 0.1%
27.41	1	< 0.1%
40.65	1	< 0.1%
50.46	1	< 0.1%
53	1	< 0.1%
57.67	1	< 0.1%
71.09	1	< 0.1%

Value	Count	Frequency (%)
6311.47	1	< 0.1%
6307.37	1	< 0.1%
6307.15	1	< 0.1%
6219.16	1	< 0.1%
6219.11	1	< 0.1%
6182.86	1	< 0.1%
6071.68	1	< 0.1%
6034.37	1	< 0.1%
6027.7	1	< 0.1%
5945.89	1	< 0.1%

out_prncp_inv
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	698
Distinct (%)	2.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	48.49969879

Minimum	0
Maximum	6307.37
Zeros	24301
Zeros (%)	97.2%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	6307.37
Range	6307.37
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	365.1731786
Coefficient of variation (CV)	7.529390651
Kurtosis	108.4974757
Mean	48.49969879
Median Absolute Deviation (MAD)	0
Skewness	9.660626381
Sum	1212443.97
Variance	133351.4504
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	24301	97.2%
1972.6	2	< 0.1%
952.95	1	< 0.1%
2110.73	1	< 0.1%
2535.55	1	< 0.1%
4602.59	1	< 0.1%
848.07	1	< 0.1%
3736.07	1	< 0.1%
1074.4	1	< 0.1%
5490.96	1	< 0.1%
Other values (688)	688	2.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	24301	97.2%
10.26	1	< 0.1%
13.28	1	< 0.1%
19.09	1	< 0.1%
27.41	1	< 0.1%
40.65	1	< 0.1%
50.46	1	< 0.1%
53	1	< 0.1%
57.67	1	< 0.1%
71.05	1	< 0.1%

Value	Count	Frequency (%)
6307.37	1	< 0.1%
6306.96	1	< 0.1%
6298.11	1	< 0.1%
6219.16	1	< 0.1%
6183.55	1	< 0.1%
6182.86	1	< 0.1%
6067.33	1	< 0.1%
6034.37	1	< 0.1%
6027.7	1	< 0.1%
5933.04	1	< 0.1%

total_pymnt
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	24098
Distinct (%)	96.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	12232.98608

Minimum	0
Maximum	58480.13992
Zeros	8
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	0
5-th percentile	1969.932888
Q1	5649.601459
median	10086.6
Q3	16568.9754
95-th percentile	30211.12113
Maximum	58480.13992
Range	58480.13992
Interquartile range (IQR)	10919.37394

Descriptive statistics

Standard deviation	8988.113395
Coefficient of variation (CV)	0.7347440221
Kurtosis	2.006942718
Mean	12232.98608
Median Absolute Deviation (MAD)	5032.58272
Skewness	1.334716695
Sum	305812419
Variance	80786182.39
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
11196.56943	19	0.1%
13263.95464	10	< 0.1%
13435.90021	10	< 0.1%
10956.77596	9	< 0.1%
13148.13786	9	< 0.1%
5478.387981	9	< 0.1%
0	8	< 0.1%
5557.025543	8	< 0.1%
11114.09033	7	< 0.1%
5598.284713	7	< 0.1%
Other values (24088)	24903	99.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	8	< 0.1%
33.73	1	< 0.1%
44.92	1	< 0.1%
44.96	1	< 0.1%
66.77	1	< 0.1%
67.32	1	< 0.1%
69.64	1	< 0.1%
69.77	1	< 0.1%
76.33	1	< 0.1%
78.93	1	< 0.1%

Value	Count	Frequency (%)
58480.13992	1	< 0.1%
56849.26986	1	< 0.1%
56199.43995	1	< 0.1%
55906.9499	1	< 0.1%
55768.77995	1	< 0.1%
54774.41992	1	< 0.1%
54714.7599	1	< 0.1%
54132.39808	1	< 0.1%
54111.73995	1	< 0.1%
54005.47996	1	< 0.1%

total_pymnt_inv
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	23961
Distinct (%)	95.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	11641.75597

Minimum	0
Maximum	58438.37
Zeros	109
Zeros (%)	0.4%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	0
5-th percentile	1497.079
Q1	5231.965
median	9453.53
Q3	15850.81
95-th percentile	29556.622
Maximum	58438.37
Range	58438.37
Interquartile range (IQR)	10618.845

Descriptive statistics

Standard deviation	8879.737938
Coefficient of variation (CV)	0.7627490183
Kurtosis	2.052566972
Mean	11641.75597
Median Absolute Deviation (MAD)	4941.15
Skewness	1.348244225
Sum	291032257.5
Variance	78849745.85
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	109	0.4%
6717.95	11	< 0.1%
11196.57	10	< 0.1%
6514.52	10	< 0.1%
13148.14	8	< 0.1%
5478.39	8	< 0.1%
7173.24	8	< 0.1%
10956.78	8	< 0.1%
14141.07	7	< 0.1%
13263.95	7	< 0.1%
Other values (23951)	24813	99.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	109	0.4%
12.65	1	< 0.1%
21.6	1	< 0.1%
25.18	1	< 0.1%
26.19	1	< 0.1%
33.73	1	< 0.1%
40.04	1	< 0.1%
44.92	1	< 0.1%
44.96	1	< 0.1%
53.95	1	< 0.1%

Value	Count	Frequency (%)
58438.37	1	< 0.1%
56515.16	1	< 0.1%
55867.02	1	< 0.1%
55579.28	1	< 0.1%
54675.68	1	< 0.1%
53954.4	1	< 0.1%
53928.33	1	< 0.1%
53118.31	1	< 0.1%
53018.62	1	< 0.1%
52880.72	1	< 0.1%

total_rec_prncp
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5238
Distinct (%)	21.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	9853.803259

Minimum	0
Maximum	35000.01
Zeros	48
Zeros (%)	0.2%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	0
5-th percentile	1400
Q1	4800
median	8002.29
Q3	13750
95-th percentile	24999.98
Maximum	35000.01
Range	35000.01
Interquartile range (IQR)	8950

Descriptive statistics

Standard deviation	7022.604905
Coefficient of variation (CV)	0.7126796345
Kurtosis	1.102268145
Mean	9853.803259
Median Absolute Deviation (MAD)	4002.29
Skewness	1.109015608
Sum	246335227.7
Variance	49316979.65
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
10000	1461	5.8%
12000	1177	4.7%
6000	1057	4.2%
5000	1051	4.2%
15000	878	3.5%
8000	798	3.2%
20000	672	2.7%
4000	582	2.3%
3000	553	2.2%
7000	538	2.2%
Other values (5228)	16232	64.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	48	0.2%
21.93	1	< 0.1%
22.5	1	< 0.1%
24.87	1	< 0.1%
30.32	1	< 0.1%
34.5	1	< 0.1%
35.14	1	< 0.1%
35.8	1	< 0.1%
38.23	1	< 0.1%
40.23	1	< 0.1%

Value	Count	Frequency (%)
35000.01	1	< 0.1%
35000	222	0.9%
34999.99	1	< 0.1%
34999.97	1	< 0.1%
34800	1	< 0.1%
34525	1	< 0.1%
34475.01	1	< 0.1%
34475	2	< 0.1%
34250	1	< 0.1%
34185.87	1	< 0.1%

total_rec_int
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	22891
Distinct (%)	91.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2280.454298

Minimum	0
Maximum	23506.56
Zeros	45
Zeros (%)	0.2%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	0
5-th percentile	191.838
Q1	679.97
median	1379.95
Q3	2855.105
95-th percentile	7549.792
Maximum	23506.56
Range	23506.56
Interquartile range (IQR)	2175.135

Descriptive statistics

Standard deviation	2596.955489
Coefficient of variation (CV)	1.138788657
Kurtosis	9.835374368
Mean	2280.454298
Median Absolute Deviation (MAD)	877.76
Skewness	2.67084385
Sum	57009077
Variance	6744177.809
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	45	0.2%
1196.57	19	0.1%
717.95	13	0.1%
1148.14	11	< 0.1%
1500.79	10	< 0.1%
1435.9	10	< 0.1%
956.78	10	< 0.1%
1263.95	10	< 0.1%
514.52	10	< 0.1%
478.39	9	< 0.1%
Other values (22881)	24852	99.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	45	0.2%
6.22	1	< 0.1%
6.27	1	< 0.1%
7.2	2	< 0.1%
8.23	1	< 0.1%
9.58	1	< 0.1%
10.26	1	< 0.1%
11.17	1	< 0.1%
11.18	1	< 0.1%
11.23	1	< 0.1%

Value	Count	Frequency (%)
23506.56	1	< 0.1%
23480.14	1	< 0.1%
22716.42	1	< 0.1%
22593.34	1	< 0.1%
22593.04	1	< 0.1%
22587.51	1	< 0.1%
22422.33	1	< 0.1%
22122.3	1	< 0.1%
21849.27	1	< 0.1%
21692.81	1	< 0.1%

total_rec_late_fee
Real number (ℝ_≥0)

ZEROS

Distinct	858
Distinct (%)	3.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.351414832

Minimum	0
Maximum	166.4297107
Zeros	23744
Zeros (%)	95.0%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0.1805519756
Maximum	166.4297107
Range	166.4297107
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	7.380823208
Coefficient of variation (CV)	5.461552613
Kurtosis	100.9457524
Mean	1.351414832
Median Absolute Deviation (MAD)	0
Skewness	8.534392604
Sum	33784.01939
Variance	54.47655122
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	23744	95.0%
15	143	0.6%
15.00000001	36	0.1%
30	32	0.1%
15.00000002	32	0.1%
14.99999999	24	0.1%
15.00000003	21	0.1%
14.99999997	20	0.1%
14.99999998	17	0.1%
15.00000004	16	0.1%
Other values (848)	914	3.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	23744	95.0%
0.01	1	< 0.1%
0.060799751	1	< 0.1%
0.101704562	1	< 0.1%
0.139999999	1	< 0.1%
0.180082904	1	< 0.1%
0.18477362	1	< 0.1%
0.27	1	< 0.1%
0.302036553	1	< 0.1%
1	1	< 0.1%

Value	Count	Frequency (%)
166.4297107	1	< 0.1%
165.69	1	< 0.1%
146.6000003	1	< 0.1%
146.04	1	< 0.1%
130.5970372	1	< 0.1%
127.7878136	1	< 0.1%
120.81	1	< 0.1%
119.9999998	1	< 0.1%
119.07	1	< 0.1%
116.1000001	1	< 0.1%

recoveries
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	2551
Distinct (%)	10.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	97.37718606

Minimum	0
Maximum	29623.35
Zeros	22375
Zeros (%)	89.5%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	372.276
Maximum	29623.35
Range	29623.35
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	709.4297238
Coefficient of variation (CV)	7.285379178
Kurtosis	388.8142305
Mean	97.37718606
Median Absolute Deviation (MAD)	0
Skewness	16.64731478
Sum	2434332.274
Variance	503290.533
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	22375	89.5%
10.07	3	< 0.1%
13.59	3	< 0.1%
24.06	2	< 0.1%
138.02	2	< 0.1%
220.23	2	< 0.1%
9.67	2	< 0.1%
9.77	2	< 0.1%
20.2	2	< 0.1%
139.62	2	< 0.1%
Other values (2541)	2604	10.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	22375	89.5%
6.3	1	< 0.1%
8.19	1	< 0.1%
8.36	1	< 0.1%
8.46	1	< 0.1%
8.56	1	< 0.1%
8.88	1	< 0.1%
8.89	1	< 0.1%
9.09	1	< 0.1%
9.11	1	< 0.1%

Value	Count	Frequency (%)
29623.35	1	< 0.1%
22943.37	1	< 0.1%
21810.31	1	< 0.1%
19508.26	1	< 0.1%
16268.35	1	< 0.1%
16066.02	1	< 0.1%
16008.02	1	< 0.1%
15914.93	1	< 0.1%
15236.31	1	< 0.1%
14906.81	1	< 0.1%

collection_recovery_fee
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED
ZEROS

Distinct	1800
Distinct (%)	7.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	12.00908462

Minimum	0
Maximum	5602.72
Zeros	22634
Zeros (%)	90.5%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	5.201
Maximum	5602.72
Range	5602.72
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	137.8508511
Coefficient of variation (CV)	11.47888082
Kurtosis	690.5619
Mean	12.00908462
Median Absolute Deviation (MAD)	0
Skewness	23.05081549
Sum	300215.1063
Variance	19002.85715
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	22634	90.5%
1.6	7	< 0.1%
0.8	7	< 0.1%
1.8	7	< 0.1%
2.02	6	< 0.1%
4.95	6	< 0.1%
3.71	6	< 0.1%
3.39	6	< 0.1%
4.73	5	< 0.1%
2.55	5	< 0.1%
Other values (1790)	2310	9.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	22634	90.5%
0.063	1	< 0.1%
0.134799995	1	< 0.1%
0.1393	1	< 0.1%
0.1952	1	< 0.1%
0.200700001	1	< 0.1%
0.23	1	< 0.1%
0.2462	1	< 0.1%
0.251699999	1	< 0.1%
0.2543	1	< 0.1%

Value	Count	Frequency (%)
5602.72	1	< 0.1%
5569.92	1	< 0.1%
5216.74	1	< 0.1%
4902.08	1	< 0.1%
4900.75	1	< 0.1%
4821.78	1	< 0.1%
4254.91	1	< 0.1%
3988.81	1	< 0.1%
3926.15	1	< 0.1%
3590.6795	1	< 0.1%

last_pymnt_d
Categorical

HIGH CARDINALITY

Distinct	101
Distinct (%)	0.4%
Missing	45
Missing (%)	0.2%
Memory size	195.4 KiB

16-May	769
13-Mar	628
13-May	586
14-Dec	553
13-Feb	548
Other values (96)	21870

Length

Max length	6
Median length	6
Mean length	5.983088884
Min length	5

Characters and Unicode

Total characters	149302
Distinct characters	32
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	< 0.1%

Sample

1st row	11-Mar
2nd row	10-Mar
3rd row	11-Dec
4th row	16-May
5th row	15-Sep

Common Values

Value	Count	Frequency (%)
16-May	769	3.1%
13-Mar	628	2.5%
13-May	586	2.3%
14-Dec	553	2.2%
13-Feb	548	2.2%
14-Jan	543	2.2%
12-Aug	543	2.2%
14-Jul	534	2.1%
12-Mar	531	2.1%
14-Mar	529	2.1%
Other values (91)	19190	76.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
16-may	769	3.1%
13-mar	628	2.5%
13-may	586	2.3%
14-dec	553	2.2%
13-feb	548	2.2%
14-jan	543	2.2%
12-aug	543	2.2%
14-jul	534	2.1%
12-mar	531	2.1%
14-mar	529	2.1%
Other values (91)	19190	76.9%

Most occurring characters

Value	Count	Frequency (%)
1	27685	18.5%
-	24954	16.7%
a	6982	4.7%
e	6109	4.1%
u	5983	4.0%
3	5940	4.0%
4	5836	3.9%
J	5797	3.9%
2	5607	3.8%
M	5065	3.4%
Other values (22)	49344	33.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	49908	33.4%
Decimal Number	49486	33.1%
Dash Punctuation	24954	16.7%
Uppercase Letter	24954	16.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	6982	14.0%
e	6109	12.2%
u	5983	12.0%
r	4377	8.8%
c	4241	8.5%
p	3941	7.9%
n	3763	7.5%
y	2688	5.4%
g	2103	4.2%
t	2039	4.1%
Other values (4)	7682	15.4%

Decimal Number

Value	Count	Frequency (%)
1	27685	55.9%
3	5940	12.0%
4	5836	11.8%
2	5607	11.3%
5	1586	3.2%
6	1273	2.6%
0	1137	2.3%
9	337	0.7%
8	85	0.2%

Uppercase Letter

Value	Count	Frequency (%)
J	5797	23.2%
M	5065	20.3%
A	4103	16.4%
D	2202	8.8%
O	2039	8.2%
F	1966	7.9%
S	1941	7.8%
N	1841	7.4%

Dash Punctuation

Value	Count	Frequency (%)
-	24954	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	74862	50.1%
Common	74440	49.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	6982	9.3%
e	6109	8.2%
u	5983	8.0%
J	5797	7.7%
M	5065	6.8%
r	4377	5.8%
c	4241	5.7%
A	4103	5.5%
p	3941	5.3%
n	3763	5.0%
Other values (12)	24501	32.7%

Common

Value	Count	Frequency (%)
1	27685	37.2%
-	24954	33.5%
3	5940	8.0%
4	5836	7.8%
2	5607	7.5%
5	1586	2.1%
6	1273	1.7%
0	1137	1.5%
9	337	0.5%
8	85	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	149302	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	27685	18.5%
-	24954	16.7%
a	6982	4.7%
e	6109	4.1%
u	5983	4.0%
3	5940	4.0%
4	5836	3.9%
J	5797	3.9%
2	5607	3.8%
M	5065	3.4%
Other values (22)	49344	33.0%

last_pymnt_amnt
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	22960
Distinct (%)	91.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2705.466391

Minimum	0
Maximum	36115.2
Zeros	45
Zeros (%)	0.2%
Negative	0
Negative (%)	0.0%
Memory size	195.4 KiB

Quantile statistics

Minimum	0
5-th percentile	44.546
Q1	224.125
median	558.56
Q3	3356.205
95-th percentile	12240.119
Maximum	36115.2
Range	36115.2
Interquartile range (IQR)	3132.08

Descriptive statistics

Standard deviation	4459.941282
Coefficient of variation (CV)	1.648492584
Kurtosis	8.83325053
Mean	2705.466391
Median Absolute Deviation (MAD)	461.63
Skewness	2.700884258
Sum	67633954.32
Variance	19891076.24
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	45	0.2%
276.06	12	< 0.1%
200	11	< 0.1%
400	10	< 0.1%
50	10	< 0.1%
500	9	< 0.1%
100	9	< 0.1%
150	8	< 0.1%
444.79	7	< 0.1%
324.42	7	< 0.1%
Other values (22950)	24871	99.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	45	0.2%
0.01	1	< 0.1%
0.16	1	< 0.1%
0.24	1	< 0.1%
0.25	1	< 0.1%
0.28	1	< 0.1%
0.35	1	< 0.1%
0.36	2	< 0.1%
0.44	3	< 0.1%
0.51	1	< 0.1%

Value	Count	Frequency (%)
36115.2	1	< 0.1%
35596.41	1	< 0.1%
35479.89	1	< 0.1%
35337.09	1	< 0.1%
35322.96	1	< 0.1%
35283.09	1	< 0.1%
35139.61	1	< 0.1%
34981.66	1	< 0.1%
34852.54	1	< 0.1%
34675.92	1	< 0.1%

next_pymnt_d
Categorical

HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	0.3%
Missing	24301
Missing (%)	97.2%
Memory size	195.4 KiB

16-Jun	688
16-Jul	10

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	4188
Distinct characters	7
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	16-Jun
2nd row	16-Jun
3rd row	16-Jun
4th row	16-Jun
5th row	16-Jun

Common Values

Value	Count	Frequency (%)
16-Jun	688	2.8%
16-Jul	10	< 0.1%
(Missing)	24301	97.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
16-jun	688	98.6%
16-jul	10	1.4%

Most occurring characters

Value	Count	Frequency (%)
u	698	16.7%
J	698	16.7%
-	698	16.7%
6	698	16.7%
1	698	16.7%
n	688	16.4%
l	10	0.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1396	33.3%
Decimal Number	1396	33.3%
Uppercase Letter	698	16.7%
Dash Punctuation	698	16.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
u	698	50.0%
n	688	49.3%
l	10	0.7%

Decimal Number

Value	Count	Frequency (%)
6	698	50.0%
1	698	50.0%

Uppercase Letter

Value	Count	Frequency (%)
J	698	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	698	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	2094	50.0%
Common	2094	50.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
u	698	33.3%
J	698	33.3%
n	688	32.9%
l	10	0.5%

Common

Value	Count	Frequency (%)
-	698	33.3%
6	698	33.3%
1	698	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4188	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
u	698	16.7%
J	698	16.7%
-	698	16.7%
6	698	16.7%
1	698	16.7%
n	688	16.4%
l	10	0.2%

last_credit_pull_d
Categorical

HIGH CARDINALITY

Distinct	102
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	195.4 KiB

16-May	6530
16-Apr	1619
16-Mar	723
13-Feb	504
16-Feb	455
Other values (97)	15168

Length

Max length	6
Median length	6
Mean length	5.993039722
Min length	5

Characters and Unicode

Total characters	149820
Distinct characters	33
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	< 0.1%

Sample

1st row	11-Jul
2nd row	10-Feb
3rd row	11-Dec
4th row	16-May
5th row	16-May

Common Values

Value	Count	Frequency (%)
16-May	6530	26.1%
16-Apr	1619	6.5%
16-Mar	723	2.9%
13-Feb	504	2.0%
16-Feb	455	1.8%
15-Dec	418	1.7%
16-Jan	412	1.6%
15-Sep	361	1.4%
13-Mar	353	1.4%
14-Mar	351	1.4%
Other values (92)	13273	53.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
16-may	6530	26.1%
16-apr	1619	6.5%
16-mar	723	2.9%
13-feb	504	2.0%
16-feb	455	1.8%
15-dec	418	1.7%
16-jan	412	1.6%
15-sep	361	1.4%
13-mar	353	1.4%
14-mar	351	1.4%
Other values (92)	13273	53.1%

Most occurring characters

Value	Count	Frequency (%)
1	26209	17.5%
-	24999	16.7%
a	11111	7.4%
M	9808	6.5%
6	9739	6.5%
y	7743	5.2%
r	4823	3.2%
e	4750	3.2%
p	4111	2.7%
A	4068	2.7%
Other values (23)	42459	28.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	49998	33.4%
Decimal Number	49824	33.3%
Dash Punctuation	24999	16.7%
Uppercase Letter	24999	16.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	11111	22.2%
y	7743	15.5%
r	4823	9.6%
e	4750	9.5%
p	4111	8.2%
u	3660	7.3%
c	2790	5.6%
n	2377	4.8%
b	1910	3.8%
o	1417	2.8%
Other values (4)	5306	10.6%

Decimal Number

Value	Count	Frequency (%)
1	26209	52.6%
6	9739	19.5%
4	3863	7.8%
5	3596	7.2%
3	3206	6.4%
2	2514	5.0%
0	523	1.0%
9	136	0.3%
8	29	0.1%
7	9	< 0.1%

Uppercase Letter

Value	Count	Frequency (%)
M	9808	39.2%
A	4068	16.3%
J	3653	14.6%
F	1910	7.6%
D	1487	5.9%
N	1417	5.7%
S	1353	5.4%
O	1303	5.2%

Dash Punctuation

Value	Count	Frequency (%)
-	24999	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	74997	50.1%
Common	74823	49.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	11111	14.8%
M	9808	13.1%
y	7743	10.3%
r	4823	6.4%
e	4750	6.3%
p	4111	5.5%
A	4068	5.4%
u	3660	4.9%
J	3653	4.9%
c	2790	3.7%
Other values (12)	18480	24.6%

Common

Value	Count	Frequency (%)
1	26209	35.0%
-	24999	33.4%
6	9739	13.0%
4	3863	5.2%
5	3596	4.8%
3	3206	4.3%
2	2514	3.4%
0	523	0.7%
9	136	0.2%
8	29	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	149820	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	26209	17.5%
-	24999	16.7%
a	11111	7.4%
M	9808	6.5%
6	9739	6.5%
y	7743	5.2%
r	4823	3.2%
e	4750	3.2%
p	4111	2.7%
A	4068	2.7%
Other values (23)	42459	28.3%

pub_rec_bankruptcies
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	3
Distinct (%)	< 0.1%
Missing	417
Missing (%)	1.7%
Memory size	195.4 KiB

0.0	23563
1.0	1014
2.0	5

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	73746
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	2.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	23563	94.3%
1.0	1014	4.1%
2.0	5	< 0.1%
(Missing)	417	1.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	23563	95.9%
1.0	1014	4.1%
2.0	5	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	48145	65.3%
.	24582	33.3%
1	1014	1.4%
2	5	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	49164	66.7%
Other Punctuation	24582	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	48145	97.9%
1	1014	2.1%
2	5	< 0.1%

Other Punctuation

Value	Count	Frequency (%)
.	24582	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	73746	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	48145	65.3%
.	24582	33.3%
1	1014	1.4%
2	5	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	73746	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	48145	65.3%
.	24582	33.3%
1	1014	1.4%
2	5	< 0.1%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	loan_amnt	funded_amnt	funded_amnt_inv	term	int_rate	installment	grade	sub_grade	emp_title	emp_length	home_ownership	annual_inc	verification_status	issue_d	loan_status	desc	purpose	title	zip_code	addr_state	dti	delinq_2yrs	earliest_cr_line	inq_last_6mths	mths_since_last_delinq	mths_since_last_record	open_acc	pub_rec	revol_bal	revol_util	total_acc	out_prncp	out_prncp_inv	total_pymnt	total_pymnt_inv	total_rec_prncp	total_rec_int	recoveries	collection_recovery_fee	last_pymnt_d	last_pymnt_amnt	next_pymnt_d	last_credit_pull_d	pub_rec_bankruptcies
0	10000	10000	9950.000000	36 months	7.51%	311.11	A	A4	15	10+ years	RENT	30000.0	Source Verified	10-Sep	Charged Off	Borrower added on 08/30/10 > thank you<br/>	home_improvement	homeimproement	076xx	NJ	5.00	0	1-Feb	3	NaN	NaN	19	0	1450	1.20%	48	0.00	0.00	2247.210000	2235.98	1509.91	350.87	386.43	3.96	11-Mar	311.11	NaN	11-Jul	0.0
1	15000	15000	14800.000000	36 months	8.94%	476.58	A	A5	1400	1 year	RENT	147000.0	Not Verified	10-Jan	Fully Paid	Borrower added on 01/14/10 > Green city housing project<br/> Borrower added on 01/23/10 > I mistyped in the application. $1400 is the current rent we pay. <br/><br/>My employer is Emerson, and my role is marketing and biz dev director. Been with them for 3 years now. My 2009 annual compensation was ~160K. <br/><br/>I have zero credit card debt or car loans. Purpose of the loan is to buy real estate in my home town in India. It costs ~$140K. Rather than taking a mortgage there, I want to buy the property outright. I used $125K from my savings, and I am short $15K. The name of the building community is Green City - www.vplprojects.com.<br/>	other	Green City	300xx	GA	3.47	0	Feb-97	0	NaN	NaN	6	0	4910	14%	17	0.00	0.00	15112.760000	14911.26	15000.00	112.76	0.00	0.00	10-Mar	15114.03	NaN	10-Feb	0.0
2	2000	2000	2000.000000	36 months	13.57%	67.94	C	C3	36000	4 years	OWN	36000.0	Not Verified	9-Oct	Fully Paid		major_purchase	payoff w/in 2 years	310xx	GA	7.83	0	Mar-00	0	NaN	NaN	8	0	1790	34.40%	10	0.00	0.00	2354.966827	2354.97	2000.00	354.97	0.00	0.00	11-Dec	101.78	NaN	11-Dec	0.0
3	35000	35000	33951.844130	60 months	20.89%	944.71	F	F1	553742017	10+ years	MORTGAGE	160000.0	Verified	11-Nov	Current	Borrower added on 11/10/11 > Consolidate all debt. On Job 27 years. Loan payment is less than 7%<br>of monthly income.<br>	debt_consolidation	Loan I	488xx	MI	12.11	0	Jun-99	1	NaN	88.0	13	2	34165	91.40%	21	5355.36	5340.00	50974.920000	48442.03	29644.65	21330.27	0.00	0.00	16-May	944.71	16-Jun	16-May	2.0
4	14000	14000	14000.000000	60 months	17.49%	351.64	D	D5	old palm inc	5 years	MORTGAGE	50000.0	Not Verified	11-Jul	Fully Paid	Borrower added on 06/29/11 > thanks for the help.<br/>	debt_consolidation	save %	334xx	FL	21.24	1	4-Jun	1	21.0	81.0	9	1	553	9.40%	27	0.00	0.00	20804.230020	20804.23	14000.00	6804.23	0.00	0.00	15-Sep	3943.27	NaN	16-May	0.0
5	12000	12000	11900.000000	36 months	8.94%	381.26	A	A5	Brocade Communications	7 years	MORTGAGE	294000.0	Not Verified	9-Dec	Fully Paid	NaN	other	Invest in Lending Club Notes	939xx	CA	0.50	0	Aug-93	0	NaN	NaN	11	0	5306	2.80%	21	0.00	0.00	12344.811770	12241.94	12000.00	344.81	0.00	0.00	10-May	11204.30	NaN	10-May	0.0
6	10000	6525	6480.473624	60 months	7.88%	131.93	A	A5	CenturyLink	4 years	MORTGAGE	65000.0	Not Verified	10-Jun	Fully Paid	Borrower added on 05/25/10 > I obtained a discover personal loan 2mths ago at a fixed rate of appx 18% for 72 mths to consolidate all revolving debt except 1 low rate card. This loan is to reduce both the term and rate of that loan in order to be debt free w/in 5 years. The only credit card balance I have is a 2nd Discover card which is a fixed balance transfer rate of 2.99% until 2013 which is being paid at a rate to accomplish $0 balance by 01/2013. Original debt was generated from costs to prepare home to sell which didn't sell. No other debt exists except fixed mortgage - not even a car payment.<br/>	credit_card	Discover	640xx	MO	7.62	1	Feb-96	1	23.0	NaN	13	0	5629	19.10%	23	0.00	0.00	7908.889997	7846.07	6525.00	1383.89	0.00	0.00	15-Feb	668.53	NaN	15-Sep	0.0
7	7800	7800	7800.000000	60 months	14.91%	185.20	D	D2	Department of Homeland Security	4 years	MORTGAGE	94000.0	Verified	11-Feb	Fully Paid	Borrower added on 01/30/11 > Money will be used to make a lump some alimony payment.<br/> Borrower added on 01/30/11 > Lump sum alimony payment.<br/> Borrower added on 01/30/11 > Average monthly breakdown:<br/><br/>Mortgage: 1206<br/><br/>Total credit card payments: 1358<br/><br/>Car/Insurance: 300<br/><br/>Miscellaneous expenses: 300<br/>	other	Help With Divorce Expenses	480xx	MI	12.96	0	Feb-00	1	NaN	NaN	11	0	2317	37.40%	37	0.00	0.00	9864.289537	9864.29	7800.00	2064.29	0.00	0.00	13-May	58.59	NaN	16-May	0.0
8	18825	18825	18825.000000	36 months	7.90%	589.04	A	A4	Down To Earth Distributors, Inc.	5 years	RENT	42000.0	Not Verified	11-Oct	Fully Paid	Borrower added on 10/03/11 > Loan to consolidate debt of a credit card and two student loans into one monthly payment. Thanks for considering investing in our financial health!<br/>	debt_consolidation	Consolidation Loan	974xx	OR	22.74	0	Aug-98	0	NaN	NaN	7	0	22121	55.40%	22	0.00	0.00	20958.528940	20958.53	18825.00	2133.53	0.00	0.00	13-Dec	239.16	NaN	13-Dec	0.0
9	35000	26675	26181.232420	60 months	11.71%	589.47	B	B3	pacific crane maintenance company	6 years	MORTGAGE	100000.0	Verified	11-Sep	Current	Borrower added on 09/14/11 > I have a great credit score, this loan fits easily in my budget, There is no chance my income will change and when my house is finished the value will be considerably higher. Thanks so much!<br/> Borrower added on 09/22/11 > Ok getting very close thanks so much!<br/>	house	home improvement	980xx	WA	1.90	0	Mar-99	0	NaN	NaN	7	0	5849	25.30%	18	2880.41	2877.69	32393.590000	31567.92	23794.59	8599.00	0.00	0.00	16-May	589.47	16-Jun	16-May	0.0

Last rows

	loan_amnt	funded_amnt	funded_amnt_inv	term	int_rate	installment	grade	sub_grade	emp_title	emp_length	home_ownership	annual_inc	verification_status	issue_d	loan_status	desc	purpose	title	zip_code	addr_state	dti	earliest_cr_line	inq_last_6mths	mths_since_last_delinq	mths_since_last_record	open_acc	pub_rec	revol_bal	revol_util	total_acc	total_pymnt	total_pymnt_inv	total_rec_prncp	total_rec_int	last_pymnt_d	last_pymnt_amnt	next_pymnt_d	last_credit_pull_d	pub_rec_bankruptcies
24989	5000	5000	4900.00000	36 months	11.48%	164.85	B	B2	PPC Construction, Inc.	8 years	RENT	48000.0	Not Verified	10-Jan	Fully Paid	Borrower added on 01/12/10 > I plan to pay off all existing credit card debts and I have not missed a payment and always make them on time.<br/>	debt_consolidation	operation debt free	900xx	CA	14.57	3-Mar	0	NaN	NaN	16	0	7479	42.70%	20	5934.555487	5815.86	5000.0	934.56	13-Feb	178.60	NaN	14-Feb	0.0
24990	13250	13250	12950.00000	36 months	10.99%	433.73	B	B3	PPC Mechanical Seals	2 years	MORTGAGE	30000.0	Source Verified	11-Jun	Fully Paid	NaN	debt_consolidation	Debt Consolidation	708xx	LA	5.88	5-Sep	0	NaN	NaN	6	0	8328	50.80%	10	15556.789530	15204.56	13250.0	2306.79	14-Jan	2590.86	NaN	16-May	0.0
24991	13000	13000	12950.00000	36 months	5.42%	392.08	A	A1	PPD	5 years	MORTGAGE	59000.0	Not Verified	11-Aug	Fully Paid	Borrower added on 08/18/11 > I want to consolidate and pay off 3 credit cards that mainly grew quickly due to unforeseen major car issues and veterinarian bills. I'm a good borrower as I always make my monthly payments and have a steady job as an enterprise mobile app systems developer.<br/>	debt_consolidation	Credit Card Payoff	284xx	NC	5.82	Sep-93	0	NaN	NaN	6	0	13331	62.60%	12	14114.794700	14060.51	13000.0	1114.79	14-Sep	401.72	NaN	15-Dec	0.0
24992	8500	8500	8500.00000	60 months	10.74%	183.72	B	B4	PPD	3 years	MORTGAGE	38000.0	Source Verified	11-Feb	Fully Paid	NaN	debt_consolidation	Credit Card Consolidation	284xx	NC	7.45	Jul-93	1	NaN	NaN	5	0	8938	51.10%	28	9990.175726	9990.18	8500.0	1490.18	13-Jan	5950.77	NaN	16-Apr	0.0
24993	14575	14575	5700.00000	60 months	13.99%	339.06	C	C3	PPD, Inc.	10+ years	RENT	45000.0	Not Verified	11-Jul	Fully Paid	Borrower added on 07/21/11 > I plan on using the funds to pay off high interest credit cards and to have one payment a month. I am a good risk based on my credit score and that I have always been current on my debt obligations. As you can see I have been with the same company for 11 years and the company is very stable and growing.<br/> Borrower added on 07/22/11 > In addition, the monthly payment on this loan is less that what I currently have been paying monthly for all my credit cards. I plan on paying the required amount every month for the loan but will often pay more than that especially when I get items such as tax returns. bonuses and employee stock sales.<br/>	debt_consolidation	Personal Loan	284xx	NC	24.96	Aug-94	1	NaN	NaN	19	0	17670	29.20%	40	16478.712190	6444.50	14575.0	1903.71	12-Aug	12752.57	NaN	16-Mar	0.0
24994	5500	5500	5500.00000	36 months	14.96%	190.55	D	D2	PPDG	7 years	MORTGAGE	52000.0	Not Verified	9-Oct	Fully Paid	554340 added on 10/10/09 > TRY TO PAY OFF ALL MY DEBT ASAP.I AM GETTING THERE SO THANKS FOR ALL YOUR SUPPORT ....LUMI	debt_consolidation	FREEDOM	320xx	FL	18.74	Aug-98	2	NaN	NaN	11	0	10655	58.20%	37	6825.066783	6825.07	5500.0	1325.07	12-May	1122.20	NaN	12-Jun	0.0
24995	11450	11450	11450.00000	36 months	8.49%	361.40	A	A5	PPG Industries	7 years	RENT	40000.0	Source Verified	11-Jun	Fully Paid	Borrower added on 06/18/11 > I've been at my job for 7 years now. I want to pay off my high interest credit cards.<br/> Borrower added on 06/21/11 > I've never been late on payments.<br/> Borrower added on 06/27/11 > I want to pay of my credit card debt fast so that I can start planning on saving for a house.<br/>	debt_consolidation	Credit Card Consolidation	980xx	WA	21.21	4-Jan	0	NaN	NaN	10	0	10192	34%	15	13010.206030	13010.21	11450.0	1560.21	14-Jul	382.90	NaN	16-May	0.0
24996	24000	24000	21100.31424	60 months	20.53%	642.96	G	G2	PPG Industries	10+ years	MORTGAGE	74454.0	Verified	10-Aug	Fully Paid	Borrower added on 08/21/10 > Consolidating all revolving debt to fixed debt and improve my great credit score to A1 status.<br/>	debt_consolidation	C3myboy	301xx	GA	19.95	Jun-98	3	NaN	NaN	9	0	29108	77.20%	24	33765.068310	26978.96	24000.0	9765.07	13-Jan	16500.39	NaN	16-May	0.0
24997	14000	14000	11411.12089	36 months	17.58%	503.19	F	F2	PPG Industries	10+ years	MORTGAGE	86000.0	Verified	9-May	Fully Paid	I'm looking to consolidate high intrest loans and improve cash flow.	debt_consolidation	consolidation loan 001	440xx	OH	21.93	Jul-99	0	NaN	101.0	13	1	18991	95%	26	17917.012900	14191.06	14000.0	3917.01	11-Oct	3857.88	NaN	15-Jun	1.0
24998	13400	13400	13400.00000	36 months	13.06%	451.89	C	C2	PPG Industries, INC	< 1 year	RENT	62040.0	Not Verified	11-Jan	Fully Paid	Borrower added on 01/26/11 > I plan to use these funds to consolidate my credit cards that I used to pay off my relocation to my new job and buy furniture for the apartment. When I get this loan I will pay a lower interest than the amount I'm currently paying on my credit cards and will have a stable payment. Even when I was a student I've never missed a payment and because I'm building credit to later on buy a house I don't plan on doing it either. PPG industries, INC is a very stable company in which many of my co-workers have been working here over 30 or 40 years. The reason is that although there not the highest payers they are over the average and like I said there very stable. I work as a Mechanical Engineer developing projects. My income every month is $5,170 that subtracting taxes, health plan, 401k, saving account and all other deductions I get net of $3,900. I pay $950 monthly rent for my apartment and an average of $100 in utilities. Most of the payments that I'm making are for the credit cards, Mint.com suggested me to consolidate with you guys to save money and if all goes well I will.<br/>	debt_consolidation	Refinance Debt Loan	706xx	LA	18.84	Sep-00	3	NaN	NaN	12	0	5389	41.80%	14	16268.440550	16268.44	13400.0	2868.44	14-Feb	475.29	NaN	14-Feb	0.0

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Decimal Number

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Decimal Number

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Lowercase Letter

Other Punctuation

Decimal Number

Open Punctuation

Math Symbol

Currency Symbol

Space Separator

Dash Punctuation

Close Punctuation

Other Symbol

Other Number

Connector Punctuation

Control

Most occurring scripts

Most frequent character per script

Latin